microbiologically influenced corrosion of 1018 …...iii abstract this research focuses on the...

MICROBIOLOGICALLY INFLUENCED CORROSION OF 1018 PLAIN CARBON STEEL IN BIODIESELS

A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

MASTER OF SCIENCE

IN

MECHANICAL ENGINEERING

December 2012

By

Corey Kaneshiro

Thesis Committee: Lloyd H. Hihara, Chairperson

Scott F. Miller Weilin Qu

ii

Acknowledgements

I would like to acknowledge my advisor, Dr. Lloyd H. Hihara, for giving me the

opportunity to work on this thesis. His expertise and guidance throughout this entire process was

critical to the success of this thesis. I would also like to thank my committee members, Dr. Scott

F. Miller and Dr. Weilin Qu.

Mr. Ryan Sugamoto and other Hawaii Corrosion Lab members have also helped me

tremendously within the lab regarding experiments, equipment use, and consultation, and for that,

I am very grateful. I am also thankful for Mr. Benjamin Respicio and Mr. Brian Kodama from

the college of engineering machine shop for their countless assistance in the fabrication of metal

coupon samples.

This research was funded by the Hawaii Natural Energy Institute at the University of

Hawaii at Manoa, and by the Office of Naval Research. Financial assistance from these agencies

is greatly acknowledged.

Lastly, I would like to thank my parents, Owen and Ann Kaneshiro, and my brother,

Tyler Kaneshiro, for their love and support throughout this critical period in my life. They have

always believed in me and pushed me to achieve my goals.

iii

Abstract

This research focuses on the microbiological effects of corrosion on 1018 plain carbon

steel immersed in biodiesels. Corrosion of steel immersed in sterilized ultra-pure water (18.2

MΩ·cm) contaminated biodiesels of 100% (B100) and 20% (B20) concentration along with

ultra-low sulfur diesel (ULSD) was initiated under three environmental conditions: anaerobic,

aerobic, and selective (sterile) aerobic. Three time exposures of 1 month, 6 months and 1 year

were conducted. Corrosion products were identified via Raman spectroscopy, x-ray diffraction,

and scanning electron microscopy equipped with an energy dispersive x-ray system. Corrosion

rates were calculated based on mass loss data obtained at the end of the 6 month and 1 year

exposure periods. Microorganism contamination was identified based on molecular biology

techniques such as colony polymerase chain reaction and DNA sequencing. pH, total acid

number, and dissolved oxygen were also measured in the fuel and water layers of the ultra-pure

water-fuel mixtures.

Raman and x-ray diffraction revealed lepidocrocite, goethite, magnetite, and iron formate

hydrate as the dominant corrosion products found on the 1018 steel coupon samples. Corrosion

rates were highest among steel coupon samples exposed in ultra-low sulfur diesel in comparison

to samples exposed in B100 and B20 fuels.

As far as microbiological contamination within samples, two different microorganisms, a

fungus, Paecilomyces variotti, and the bacteria Ralstonia solanacearum were successfully

cultured and isolated from the fuel-water interface and water layer of the B20 and ULSD fuel-

water mixtures in the experiment. Microbiological effects in the form of sludge was observed

only on 1018 steel coupons exposed in the B20 fuel-water mixtures set in an aerobic

environment.

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Contents Acknowledgements ....................................................................................................................... ii Abstract ......................................................................................................................................... iii Contents ........................................................................................................................................ iv List of Figures ............................................................................................................................... vi List of Tables .............................................................................................................................. xiv Chapter 1 ....................................................................................................................................... 1 Introduction ................................................................................................................................... 1

1.1 Objectives of this Study ................................................................................................... 2 Chapter 2 ....................................................................................................................................... 3 Literature Review ......................................................................................................................... 3

2.1 Introduction ...................................................................................................................... 3 2.2 Biodiesels ......................................................................................................................... 5 2.3 Biocorrosion/MIC .......................................................................................................... 10 2.4 Biofilm ........................................................................................................................... 11 2.5 Case Studies ................................................................................................................... 11

Chapter 3 ..................................................................................................................................... 14 Materials and Methods ............................................................................................................... 14

3.1. Introduction .................................................................................................................... 14 3.2. Materials Used................................................................................................................ 14 3.3. Experimental Setup ........................................................................................................ 15 3.4. pH Measurements ........................................................................................................... 17 3.5. Dissolved Oxygen (DO) Measurements ........................................................................ 18 3.6. Total Acid Number Measurements ................................................................................ 19 3.7. Microbial Contamination ............................................................................................... 19 3.8. Corrosion Product Characterization – Raman Spectroscopy ......................................... 23 3.9. Corrosion Product Characterization – Scanning Electron Microscope (SEM) .............. 24 3.10. Corrosion Product Characterization – X-Ray Diffraction (XRD) .............................. 25 3.11. Weight Loss Technique .............................................................................................. 26

Chapter 4 ..................................................................................................................................... 27 Thermodynamics of Iron ............................................................................................................ 27

v

Chapter 5 ..................................................................................................................................... 35 Corrosion Product Characterization ........................................................................................ 35

5.1. Introduction .................................................................................................................... 35 5.2. Corrosion Product Morphology ..................................................................................... 35 5.3. Raman Spectroscopy ...................................................................................................... 44 5.4. XRD ............................................................................................................................... 61 5.5. SEM/EDXA ................................................................................................................... 78

Chapter 6 ..................................................................................................................................... 86 pH, TAN, DO and Mass Loss ..................................................................................................... 86

6.1. pH ................................................................................................................................... 86 6.2. TAN ................................................................................................................................ 89 6.3. DO .................................................................................................................................. 96 6.4. Mass Loss ....................................................................................................................... 98

Chapter 7 ................................................................................................................................... 103 Microbial Contamination ......................................................................................................... 103 Chapter 8 ................................................................................................................................... 110 Summary .................................................................................................................................... 110 References .................................................................................................................................. 120 Appendix .................................................................................................................................... 123

vi

List of Figures

Figure 1. Experimental setup of fuel-water mixtures with 1018 steel coupons immersed. Left to right: B100/water mixture, B20/water mixture, and ULSD/water mixture. ................................. 15 Figure 2. B100/water fuel mixture depicting anaerobic, aerobic, and selective aerobic environments. Anaerobic cap and selective aerobic cap depicted. ............................................... 16 Figure 3. 108 samples loaded in boxes to be exposed outdoors for six months and one year. ..... 17 Figure 4. pH measurement setup. ................................................................................................. 18 Figure 5. DO experimental setup. ................................................................................................. 18 Figure 6. Dexsil TAN kit. ............................................................................................................. 19 Figure 7. Bacteria sample, 16S rRNA sequencing yields a 65% match to the bacterial species Bacillus licheniformis. .................................................................................................................. 20 Figure 8. Bacteria sample, 16S rRNA sequencing yields a 98% match to the bacterial species Aeromicrobium tamlense. ............................................................................................................. 21 Figure 9. Bacteria sample, 16S rRNA sequencing yields a 98% match to the bacterial species Bacillus horikoshi. ........................................................................................................................ 21 Figure 10. Bacteria sample, 16S rRNA sequencing yields a 93% match to the bacterial species Bacillus novalis. ............................................................................................................................ 22 Figure 11. Eppendorf thermo cycler. ............................................................................................ 23 Figure 12. Raman spectroscopy setup. ......................................................................................... 24 Figure 13. SEM/EDXA setup. ...................................................................................................... 25 Figure 14. XRD analysis setup. .................................................................................................... 25 Figure 15. 6 month steel coupon samples exposed in an anaerobic environment segregated by type of fuel. ................................................................................................................................... 36 Figure 16. 6 month steel coupon samples exposed in an aerobic environment segregated by type of fuel. ........................................................................................................................................... 37 Figure 17. 6 month steel coupon samples exposed in a selective aerobic environment segregated by type of fuel. .............................................................................................................................. 38

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Figure 18. 1 year steel coupon samples exposed in an anaerobic environment segregated by type of fuel. ........................................................................................................................................... 39 Figure 19. 1 year steel coupon samples exposed in an aerobic environment segregated by type of fuel. ............................................................................................................................................... 40 Figure 20. 1 year steel coupon samples exposed in a selective aerobic environment segregated by type of fuel. ................................................................................................................................... 41 Figure 21. Microbial contamination in the form of sludge on 1018 steel coupon exposed in filtered/unfiltered B20 fuel-water mixture in aerobic environment. ............................................. 43 Figure 22. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered B100 fuel samples in anaerobic (1UC61), selective aerobic (1UM63), and aerobic (1UO61) environments........................................................................................................................................................ 44 Figure 23. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered B100 fuel samples in anaerobic (1FC63), selective aerobic (1FM63), and aerobic (1FO62) environments. 45 Figure 24. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered B20 fuel samples in anaerobic (2UC62) and selective aerobic (2UM63) environments. ........................... 46 Figure 25. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered B20 fuel samples in anaerobic (2FC63) and selective aerobic (2FM61) environments. ............................. 47 Figure 26. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel samples in anaerobic (3UC61 and 3UC63) environments. ........................................................... 48 Figure 27. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered ULSD fuel samples in anaerobic (3FC61 and 3FC63) environments. ............................................................ 49 Figure 28. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in selective aerobic (3FM63 and 3UM61) environments. ........... 50 Figure 29. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in aerobic (3FO63 and 3UO61) environments. ........................... 51 Figure 30. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered B100 fuel samples in anaerobic (1FC13 and 1UC12) environments. .......................................... 52 Figure 31. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered B100 fuel samples in selective aerobic (1FM12 and 1UM11) environments. ............................. 53 Figure 32. Raman spectroscopy of 1 year 1018 steel coupons exposed in unfiltered B100 fuel samples in an aerobic (1UO12) environment. .............................................................................. 54

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Figure 33. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered B100 fuel samples in an aerobic (1FO12) environment. ............................................................................... 55 Figure 34. Raman spectroscopy of 1 year 1018 steel coupons exposed in unfiltered B20 fuel samples in anaerobic (2UC12) and selective aerobic (2UM11) environments. ........................... 56 Figure 35. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered B20 fuel samples in anaerobic (2FC13) and selective aerobic (2FM13) environments. ............................. 57 Figure 36. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in anaerobic (3FC13, 3FC11, and 3UC11) environments. ........................... 58 Figure 37. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in selective aerobic (3FM13 and 3UM11) environments. ............................ 59 Figure 38. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in aerobic (3FO12 and 3UO11) environments. ............................................ 60 Figure 39. XRD of 6 months 1018 steel coupons exposed in unfiltered B100 fuel samples in anaerobic (1UC61), selective aerobic (1UM63), and aerobic (1UO61) environments. ............... 61 Figure 40. XRD of 6 months 1018 steel coupons exposed in filtered B100 fuel samples in anaerobic (1FC63), selective aerobic (1FM63), and aerobic (1FO62) environments. ................. 62 Figure 41. XRD of 6 months 1018 steel coupons exposed in unfiltered B20 fuel samples in anaerobic (2UC62) and selective aerobic (2UM63) environments. ............................................. 63 Figure 42. XRD of 6 months 1018 steel coupons exposed in filtered B20 fuel samples in anaerobic (2FC63) and selective aerobic (2FM61) environments. ............................................... 64 Figure 43. XRD of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel samples in an anaerobic (3UC61 and 3UC63) environment. .............................................................................. 65 Figure 44. XRD of 6 months 1018 steel coupons exposed in filtered ULSD fuel samples in an anaerobic (3FC61 and 3FC63) environment. ................................................................................ 66 Figure 45. XRD of 6 months 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in a selective aerobic (3FM63 and 3UM61) environment. ............................................. 67 Figure 46. XRD of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel samples in an aerobic (3UO61) environment. ..................................................................................................... 68 Figure 47. XRD of 6 months 1018 steel coupons exposed in filtered ULSD fuel samples in an aerobic (3FO63) environment. ...................................................................................................... 69

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Figure 48. XRD of 1 year 1018 steel coupons exposed in unfiltered B100 fuel samples in an anaerobic (1UC12), selective aerobic (1UM11), and aerobic (1UO12) environments. ............... 70 Figure 49. XRD of 1 year 1018 steel coupons exposed in filtered B100 fuel samples in an anaerobic (1FC13), selective aerobic (1FM12), and aerobic (1FO12) environments. ................. 71 Figure 50. XRD of 1 year 1018 steel coupons exposed in unfiltered B20 fuel samples in an anaerobic (2UC12) and selective aerobic (2UM11) environment. ............................................... 72 Figure 51. XRD of 1 year 1018 steel coupons exposed in filtered B20 fuel samples in an anaerobic (2UC12) and selective aerobic (2UM11) environment. ............................................... 73 Figure 52. XRD of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in an anaerobic (3FC11, 3FC13, and 3UC11) environment. .......................................... 74 Figure 53. XRD of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in a selective aerobic (3UM11 and 3FM13) environment. ............................................. 75 Figure 54. XRD of 1 year 1018 steel coupon exposed in unfiltered ULSD fuel samples in an aerobic (3UO11) environment. ..................................................................................................... 76 Figure 55. XRD of 1 year 1018 steel coupon exposed in filtered ULSD fuel samples in an aerobic (3FO12) environment. ...................................................................................................... 77 Figure 56. SEM analysis of 1018 steel coupon (1UC61) exposed in unfiltered B100 fuel-water mixture exposed in an anaerobic environment. ............................................................................ 79 Figure 57. SEM analysis of 1018 steel coupon (2FC63) exposed in filtered B20 fuel-water mixture exposed in an anaerobic environment. ............................................................................ 80 Figure 58. SEM analysis of 1018 steel coupon (3UO61) exposed in unfiltered ULSD fuel-water mixture exposed in an aerobic environment. ................................................................................ 81 Figure 59. SEM analysis of 1018 steel coupon (3UC11) exposed in unfiltered ULSD fuel-water mixture exposed in an anaerobic environment. ............................................................................ 82 Figure 60. SEM analysis of 1018 steel coupon (1UO12) exposed in unfiltered B100 fuel-water mixture exposed in an aerobic environment. ................................................................................ 83 Figure 61. SEM analysis of 1018 steel coupon (3FO12) exposed in filtered ULSD fuel-water mixture exposed in an aerobic environment. ................................................................................ 84 Figure 62. 6 month plot of TAN vs. pH of fuels in an anaerobic environment. ........................... 89 Figure 63. 6 month plot of TAN vs. pH of fuels in an aerobic environment. ............................... 90

x

Figure 64. 6 month plot of TAN vs. pH of fuels in a selective aerobic environment. .................. 90 Figure 65. 1 year plot of TAN vs. pH of fuels in an anaerobic environment. .............................. 91 Figure 66. 1 year plot of TAN vs. pH of fuels in an aerobic environment. .................................. 91 Figure 67. 1 year plot of TAN vs. pH of fuels in a selective aerobic environment. ..................... 92 Figure 68. Plot of pH and TAN values for 6 month anaerobic environment. ............................... 93 Figure 69. Plot of pH and TAN values for 6 month aerobic environment. .................................. 93 Figure 70. Plot of pH and TAN values for 6 month selective aerobic environment. ................... 94 Figure 71. Plot of pH and TAN values for 1 year anaerobic environment. .................................. 94 Figure 72. Plot of pH and TAN values for 1 year aerobic environment. ...................................... 95 Figure 73. Plot of pH and TAN values for 1 year selective aerobic environment. ....................... 95 Figure 74. Fungi culture, 18S rRNA sequencing yields a 99% match to the fungi Paecilomyces saturatus. ..................................................................................................................................... 103 Figure 75. Bacteria isolate, 16S rRNA sequencing yields a 97% match to the bacteria Ralstonia solanacearum. ............................................................................................................................. 106 Figure 76. Gel electrophoresis of colony PCR products from bacteria isolate. .......................... 107 Figure 77. Before and after acetone wash image of 1018 steel coupon exposed in B20 fuel-water mixture exposed in an aerobic environment. .............................................................................. 112 Figure 78. Penetration rate vs. pH (fuel layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B100 fuel-water mixtures. ....................... 116 Figure 79. Penetration rate vs. pH (water layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B100 fuel-water mixtures. ....................... 116 Figure 80. Penetration rate vs. TAN of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B100 fuel-water mixtures. ................................................. 116 Figure 81. Penetration rate vs. pH (fuel layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B20 fuel-water mixtures. ......................... 117 Figure 82. Penetration rate vs. pH (water layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B20 fuel-water mixtures. ......................... 117

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Figure 83. Penetration rate vs. TAN of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered B20 fuel-water mixtures. ................................................... 117 Figure 84. Penetration rate vs. pH (fuel layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered ULSD fuel-water mixtures. ..................... 118 Figure 85. Penetration rate vs. pH (water layer) of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered ULSD fuel-water mixtures. ..................... 118 Figure 86. Penetration rate vs. TAN of 1018 steel exposed in all environmental conditions for 6 months/1 year in filtered/unfiltered ULSD fuel-water mixtures. ................................................ 118 Figure A1. SEM analysis of 1018 steel coupon (1UC61) exposed in unfiltered B100 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 124 Figure A2. SEM analysis of 1018 steel coupon (1UO61) exposed in unfiltered B100 fuel-water mixture exposed in an aerobic environment. .............................................................................. 125 Figure A3. SEM analysis of 1018 steel coupon (1UM63) exposed in unfiltered B100 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 126 Figure A4. SEM analysis of 1018 steel coupon (1FC63) exposed in filtered B100 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 127 Figure A5. SEM analysis of 1018 steel coupon (1FO62) exposed in filtered B100 fuel-water mixture exposed in an aerobic environment. .............................................................................. 128 Figure A6. SEM analysis of 1018 steel coupon (1FM63) exposed in filtered B100 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 129 Figure A7. SEM analysis of 1018 steel coupon (2UC62) exposed in unfiltered B20 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 130 Figure A8. SEM analysis of 1018 steel coupon (2UM63) exposed in unfiltered B20 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 131 Figure A9. SEM analysis of 1018 steel coupon (2FC63) exposed in filtered B20 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 132 Figure A10. SEM analysis of 1018 steel coupon (2FM61) exposed in filtered B20 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 133 Figure A11. SEM analysis of 1018 steel coupon (3UC61) exposed in unfiltered ULSD fuel-water mixture exposed in an anaerobic environment. .......................................................................... 134

xii

Figure A12. SEM analysis of 1018 steel coupon (3UO61) exposed in unfiltered ULSD fuel-water mixture exposed in an aerobic environment. .............................................................................. 135 Figure A13. SEM analysis of 1018 steel coupon (3UM61) exposed in unfiltered ULSD fuel-water mixture exposed in a selective aerobic environment. ....................................................... 136 Figure A14. SEM analysis of 1018 steel coupon (3FC61) exposed in filtered ULSD fuel-water mixture exposed in an anaerobic environment. .......................................................................... 137 Figure A15. SEM analysis of 1018 steel coupon (3FO63) exposed in filtered ULSD fuel-water mixture exposed in an aerobic environment. .............................................................................. 138 Figure A16. SEM analysis of 1018 steel coupon (3FM63) exposed in filtered ULSD fuel-water mixture exposed in a selective aerobic environment. ................................................................. 139 Figure A17. SEM analysis of 1018 steel coupon (1UC12) exposed in unfiltered B100 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 140 Figure A18. SEM analysis of 1018 steel coupon (1UO12) exposed in unfiltered B100 fuel-water mixture exposed in an aerobic environment. .............................................................................. 141 Figure A19. SEM analysis of 1018 steel coupon (1UM11) exposed in unfiltered B100 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 142 Figure A20. SEM analysis of 1018 steel coupon (1FC13) exposed in filtered B100 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 143 Figure A21. SEM analysis of 1018 steel coupon (1FO12) exposed in filtered B100 fuel-water mixture exposed in an aerobic environment. .............................................................................. 144 Figure A22. SEM analysis of 1018 steel coupon (1FM12) exposed in filtered B100 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 145 Figure A23. SEM analysis of 1018 steel coupon (2UC12) exposed in unfiltered B20 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 146 Figure A24. SEM analysis of 1018 steel coupon (2UM11) exposed in unfiltered B20 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 147 Figure A25. SEM analysis of 1018 steel coupon (2FC13) exposed in filtered B20 fuel-water mixture exposed in an anaerobic environment. .......................................................................... 148 Figure A26. SEM analysis of 1018 steel coupon (2FM13) exposed in filtered B20 fuel-water mixture exposed in a selective aerobic environment. ................................................................. 149

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Figure A27. SEM analysis of 1018 steel coupon (3UC11) exposed in unfiltered ULSD fuel-water mixture exposed in an anaerobic environment. .......................................................................... 150 Figure A28. SEM analysis of 1018 steel coupon (3UO11) exposed in unfiltered ULSD fuel-water mixture exposed in an aerobic environment. .............................................................................. 151 Figure A29. SEM analysis of 1018 steel coupon (3UM11) exposed in unfiltered ULSD fuel-water mixture exposed in a selective aerobic environment. ....................................................... 152 Figure A30. SEM analysis of 1018 steel coupon (3FC13) exposed in filtered ULSD fuel-water mixture exposed in an anaerobic environment. .......................................................................... 153 Figure A31. SEM analysis of 1018 steel coupon (3FO12) exposed in filtered ULSD fuel-water mixture exposed in an aerobic environment. .............................................................................. 154 Figure A32. SEM analysis of 1018 steel coupon (3FM13) exposed in filtered ULSD fuel-water mixture exposed in a selective aerobic environment. ................................................................. 155

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List of Tables

Table 1. Chemical composition of selected specifications and 1018 steel. .................................. 14 Table 2. Experimental design. ...................................................................................................... 16 Table 3. Equilibrium potential of −°

OHO /2φ for various pH values. .............................................. 29

Table 4. Equilibrium potential of

FeFe /2+°φ for various pH values. ............................................... 30 Table 5. Overall electrochemical cell potential for various pH values. ........................................ 30 Table 6. Equilibrium potential of

2/ HH +φ for various pH values. .................................................. 32


FeFe /2+°φ for various pH values. ............................................... 33 Table 8. Overall electrochemical cell potential for various pH values. ........................................ 33 Table 9. pH results for 6 month steel coupon samples exposed in an anaerobic environment. ... 86 Table 10. pH results for 6 month steel coupon samples exposed in an aerobic environment. ..... 86 Table 11. pH results for 6 month steel coupon samples exposed in a selective aerobic environment. ................................................................................................................................. 86 Table 12. pH results for B100, B20, and ULSD as received straight from the pump. ................. 86 Table 13. pH results for 1 year steel coupon samples exposed in an anaerobic environment. ..... 87 Table 14. pH results for 1 year steel coupon samples exposed in an aerobic environment. ......... 87 Table 15. pH results for 1 year steel coupon samples exposed in a selective aerobic environment........................................................................................................................................................ 88 Table 16. pH results for 1 year old B100, B20, and ULSD fuels. ................................................ 88 Table 17. 6 month TAN results for fuels in an anaerobic, aerobic, and selective aerobic environment. ................................................................................................................................. 89 Table 18. 1 year TAN results for fuels in an anaerobic, aerobic, and selective aerobic environment. ................................................................................................................................. 91 Table 19. DO results for B100 fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment. ................................................................................................................................. 96

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Table 20. DO results for B20 fuel fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment. ................................................................................................................. 97 Table 21. DO results for ULSD fuel fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment. ................................................................................................................. 97 Table 22. Mass loss results for 1018 steel coupons exposed for 6 months in unfiltered fuels in an aerobic, selective aerobic, and anaerobic environment. ............................................................... 98 Table 23. Mass loss results for 1018 steel coupons exposed for 6 months in filtered fuels in an aerobic, selective aerobic, and anaerobic environment. ............................................................... 99 Table 24. Mass loss results for 1018 steel coupons exposed for 1 year in unfiltered fuels in an aerobic, selective aerobic, and anaerobic environment. ............................................................. 100 Table 25. Mass loss results for 1018 steel coupons exposed for 1 year in filtered fuels in an aerobic, selective aerobic, and anaerobic environment. ............................................................. 101 Table 26. Summary of corrosion product found on 1018 steel coupons via Raman and XRD exposed in all environmental conditions for 6 months and 1 year. ............................................ 114

1

Chapter 1

Introduction

The production of biodiesel fuels has emerged as an alternative fuel of petroleum diesel

worldwide. Cleaner emissions and availability are known advantages of using biodiesels.

Biodiesels are essentially ester-based fuels derived from vegetable oils or animal fats through a

transesterification process [1]. Few studies have taken into consideration the biological nature of

biodiesels and their corrosive effects in the pipeline transportation and long-term storage sectors.

Corrosion is defined as the deterioration of metals which is caused by electrochemical

processes in which electrons are transferred to an external electron acceptor causing the release

of the metal ions into the surrounding medium [2]. Literature has shown that microbiologically

influenced corrosion (MIC) enhances or accelerates corrosion. MIC is also caused by

electrochemical processes where microorganisms accelerate the corrosion of metals [3]. The

microorganisms of primary interest in this research are bacteria.

2

1.1 Objectives of this Study

This project is a comprehensive study to elucidate the effects of biodiesel on MIC of

1018 plain-carbon steel that are typically used for pipelines, storage tanks, and fuel tanks.

Corrosion testing and microbial analysis will encompass a biodiesel-freshwater system.

3

Chapter 2

Literature Review

2.1 Introduction

Microbiologically influenced corrosion (MIC) is an electrochemical process where

microorganisms initiate, facilitate, or accelerate a corrosion reaction on a metal surface [3].

There are three types of microorganisms. These include bacteria, fungi, and algae. Bacteria will

be the focus in this project. Bacteria are ubiquitous single-celled prokaryotic organisms. They

vary in size and shape, each having its own characteristics. Some bacteria are pathogenic, but the

majority is beneficial to us and the environment.

In MIC, sulfur-reducing bacteria (SRB) are the most notable and have been shown to

accelerate corrosion [2]. These types of bacteria are anaerobic and produce hydrogen sulfide

which acidifies the environment. They are also responsible for catalyzing the penetration of

hydrogen into steels, a phenomenon known as sulfide-induced stress cracking. One theory

suggests SRBs utilize molecular hydrogen resulting from the following anodic and cathodic

reactions shown below.

Fe → Fe2+ + 2e- (Anodic)

2H+ + 2e- → H2 (Cathodic)

or

2H2S + 2e- → 2HS- + H2 (Cathodic)

This removal of hydrogen is termed cathodic depolarization as it facilitates the electrochemical

cathodic reaction which is considered the controlling step in the overall corrosion process [4]. A

second theory suggests that SRBs stimulate corrosion by anodic depolarization [4]. This is

4

possible by the localized acidification at the anode which results from the formation of iron

sulfide corrosion products as depicted by the reaction below.

Fe2+ + HS- → FeS + H+

Both theories result in the production of sulfide which results in the precipitation of ferrous

sulfide corrosion products within the anoxic regions of the biofilm. Both reduced ferrous and

sulfide ions are subject to oxidation across the biofilm interface which in turn generates further

corrosion products of the form ferric oxide and or hydroxide and elemental sulfur as shown by

the reaction below [4].

S + H2O + 2e- → HS- + OH-

Corrosion products ferric oxide and or hydroxide and elemental sulfur are often indicative of

active SRB corrosion [4]. SRBs are just one type of bacteria which have been shown to

accelerate corrosion. Others include sulfur-oxidizing bacteria, iron-oxidizing/reducing bacteria,

manganese-oxidizing bacteria, and bacteria secreting organic acids and slime [2].

The organic nature of biodiesels makes it a prime target for microbial contamination

mainly in the form of bacteria. Bacteria are able to survive in these fuels whenever there is the

presence of water. Microorganisms generally flourish in the water phase, but feed on fuel at the

water-fuel phase boundary [5]. Contamination of fuel by microorganisms can cause biofouling.

Whenever biofouling occurs, an extracellular polymeric substance is formed at the fuel-water

interface. This is more commonly known as the biofilm. The term biofilm refers to the

development of microbial communities on submerged surfaces in aqueous environments [6].

Thus, a bacterial consortium is formed and corrosion is accelerated due to the variety of bacteria

present.

5

2.2 Biodiesels

Biodiesel can be used in its pure form (B100) or blended with petroleum diesel as another

source of renewable energy. Biodiesel, in comparison to petroleum fuel, has the advantage of

being biodegradable and non-toxic, having higher flash point, and causing reduced emissions.

However, the major cons of biodiesel include its oxidative instability, poorer low-temperature

properties, slightly lower power and torque generation, and higher fuel consumption [7].

Biodiesel is synthesized from vegetable oils and or animal fats which mainly contain

triglyceride molecules. Unfortunately, glycerides cause the natural oils to thicken and become

sticky; hence the natural oils are converted from triglycerides into three mono-alkyl esters via

transesterification. The glycerol is removed as a by-product and the esters that remain comprise

the biodiesel. Hence, biodiesel can be synthesized from many different types of natural oils and

as a result many acronyms are used to describe their origins: For example, they are soybean

methyl ester (SME), rapeseed methyl ester (RME), fatty acid methyl ester (FAME), and palm oil

methyl ester (POME) to name a few. A study has shown that the fatty acid profiles of biodiesels

differ based on the source. Biodiesel from coconut oil, palm oil, and tallow contained more

saturated acids; whereas, biodiesel from soybean, sunflower, rapeseed, calona, etc. contained

more unsaturated fatty acids [7]. Therefore, it can be expected that coconut or palm oil based

biodiesels are less prone to oxidation than biodiesels based on sources that contain higher

amounts of unsaturated acids.

A number of studies have also been conducted to assess biodiesel compatibility with

different materials. In one study, petroleum diesel, a soybean-derived biodiesel, and a sunflower-

derived biodiesel were tested for material compatibility against structural carbon steel (ASTM

A36) and high density polyethylene (HDPE) [8]. Weight loss data for the samples over a 60 and

6

115 day immersion revealed that time is a relevant factor in diesel-fuel action on the carbon steel,

which experienced a fourfold weight loss between the two time periods. The soybean-derived

biodiesel was also found to be more compatible with carbon steel than the petroleum diesel and

sunflower biodiesel. Immersion experiments regarding the HDPE revealed a significant weight

gain instead of a mass loss. The HDPE immersed in petroleum diesel showed the highest weight

gain, while those immersed in the other two biodiesels show minimum weight gain. In terms of

fuel ageing, Fourier transform infrared spectroscopy (FTIR) was used to monitor the different

fuels before and after their immersion experiments. Surprisingly, ageing was shown to take place

only in the biodiesels which had very little effect on the degradation of the carbon steel and

HDPE. The petroleum diesel, which did not age, was the most aggressive towards the steel and

HDPE.

In 2007, a study on the corrosion rates of a piston metal and piston liner metal immersed

in biodiesel originating from various seed oils (Pongamia glabra, Salvadora oleoides, Madhuca

Indica, and Jatropha curcas) revealed that the biodiesel comprised of Salvadora oil was the most

aggressive leading to the corrosion rate for the piston metal and piston liner metal of 0.1236 and

0.1329 mpy respectively [9]. Interestingly, petroleum diesel showed low corrosivity and was tied

with biodiesel comprised of Pongamia and Madhuca oil as having the lowest corrosion rates for

piston metal and piston liner metal of 0.0058 and 0.0065 mpy, respectively. Kaul et al [9]

attributed the higher corrosivity of the biodiesel comprised of Salvadora oil to the higher

percentage of sulphur content.

Another study in 2008 tested the corrosive effects of biodiesel derived from rice husk on

aluminum, mild steel (Q235A), brass (H62), and austenite stainless steel (SS321, 1Cr18Ni9Ti)

[10]. Three bio-oil-diesel emulsions were used which were 100% biodiesel, 30% biodiesel, and

7

10% biodiesel. Capped 50 mL glass bottles were used to hold the metal samples whereupon the

coupons were immersed in their respective fuel emulsions. The bottles were then placed at room

temperature (25°C), 50°C, and 70°C with weight loss data of the coupons taken at intervals of 6,

12, 24, 48, 72, and 120 h. It was reported that the most significant weight loss was observed for

mild steel, followed by aluminum, while brass exhibited only slight weight loss. Also, for

elevated temperatures, the weight loss rates were found to greatly increase. Stainless steel was

not affected under any of the conditions. The 100% biodiesel fuel was found to be the most

corrosive followed by the emulsions with 30% biodiesel and 10% biodiesel. Qiang et al [10]

attributed this to the fact that the 10% and 30% emulsions of bio-oil with diesel have a limited

contact area between the metal surfaces since the diesel is the continuous phase in the emulsions.

In 2010, Haseeb et al [11] investigated the corrosion behavior of copper and bronze in

diesel and palm biodiesel. Static immersions of test coupons were conducted at two different

temperatures, room temperature (25 - 30°C) and 60°C. At room temperature, the fuels tested

were diesel, 50% palm biodiesel, and 100% palm biodiesel for an exposure time of 2640 h. At

60°C, diesel, 100% palm biodiesel and 100% oxidized palm biodiesel were tested for an

exposure time of 840 h. Copper was shown to have higher corrosion rates in comparison to

leaded bronze. A corrosion rate of 0.042 compared to 0.018 mpy for 100% palm biodiesel at

room temperature and 0.053 versus 0.023 mpy for 100% palm biodiesel at 60°C. It is believed

that the improved corrosion resistance of bronze is due to the presence of alloying elements such

as tin (Sn) [9]. Kaul et al [9] also noted that biodiesel exposed to different metals showed

significant degradation, as evidenced by an increased TAN (total acid number), oxidation

product rate, along with free water content with increasing concentration of biodiesel in blends.

The permissible TAN as stated by ASTM standard D6751 is 0.8 mg KOH/g. It was found that

8

the TAN values of diesel when exposed to copper and bronze for 2640 h remained relatively

constant at a value of approximately 0.25. When copper and bronze were exposed to 50% and

100% palm biodiesel, there was an increase in TAN after the exposure. This was especially true

for 100% palm biodiesel, where the TAN increased from an initial 0.5 to approximately 1.1. As

stated before, the permissible TAN as stated by ASTM standard D6751 is 0.8 mg KOH/g which

was clearly exceeded in the case of the copper and bronze coupons exposed in the 100% palm

biodiesel for only 2640 h. Thus, it can be seen that increased TAN indicate the oxidation of

biodiesel [9].

In 2010, Fazal et al [12] performed an investigation on the corrosion behavior of copper

(99.99% pure), aluminum (99% pure), and stainless steel (316) in diesel and palm biodiesel. Test

coupons were immersed in both diesel and palm biodiesel (continually stirred at 250 rpm) at

80°C for 1200 h. The results revealed that copper had the highest corrosion rate of 0.586 mpy

followed by aluminum with 0.202 mpy and stainless steel having the lowest at 0.015 mpy.

Copper again was shown to have the highest TAN which suggests that copper acts as a strong

catalyst to oxidize the biodiesel. Also, it was noted that the difference in TAN between stainless

steel and copper exposed biodiesel was very small, but the difference in their respective

corrosion rates varied greatly. This suggests that the corrosiveness of the fuel is the same, but the

copper is less resistant compared to the stainless steel. There is no strong correlation between the

change in the acid number and the degree of corrosion on the exposed metal. Similarly in 2012,

Fazal et al [13] set out to investigate the degradation mechanism of different automotive

materials such as copper, brass, aluminum, and cast iron by characterizing the corrosion products.

The corrosion effects of palm biodiesel and diesel at room temperature (25 - 27°C) for an

exposure time of 2880 h was investigated. The corrosion rates were found to be the following for

9

copper, brass, aluminum, and cast iron: 0.39278, 0.209898, 0.173055, and 0.112232 mpy

respectively for palm biodiesel. In the case of diesel, the rates were the following for copper,

brass, aluminum, and cast iron: 0.158296, 0.120122, 0.084055, and 0.77402 mpy respectively.

Thus, it was shown that palm biodiesel was more corrosive than diesel, and that copper showed

the most severe corrosion.

Biodiesel has a higher affinity toward moisture content in comparison to petroleum diesel,

and the water retaining capacity of biodiesel is much higher than diesel [14]. The hygroscopic

fatty acid methyl ester (FAME) compounds are the primary reason for biodiesel being much

more hydrophilic than diesel. Although the maximum water content allowed by ASTM standard

D6751 is 500 mg·kg-1, water contamination often occurs in storage, where temperature and

humidity greatly affect the amount of excess water absorbed within the surrounding environment.

Water contamination within biodiesel also poses a serious problem as it harbors and facilitates

the growth of microorganisms which could then lead to the corrosion of metals, and the

formation of sludge and slime, thereby constricting fuel filters and fuel lines. [5, 14]. Water at

high temperatures has also been shown to hydrolyze esters as well as triglycerides and produce

different types of fatty acids which are more corrosive [11].

Therefore, a study in 2012 was carried out to determine the water absorbance of samples

of biodiesel and biodiesel-diesel fuel blends by evaluating the temperature and blend ratio

parameters [14]. Diesel and Brazilian biodiesel and subsequent blends in the form of 5%, 10%,

20%, 40%, 60%, 80%, and 100% biodiesel were the fuels tested. The methods employed to

measure water content consisted of the Karl Fischer measurement, moisture absorption, turbidity

measurements (clear and bright test), and high-temperature simulated distillation gas

chromatography. The results revealed that the water absorption capacity of 100% biodiesel and

10

diesel oil rapidly decrease if the temperature drops. At a temperature of 293.15 and 323.15 K,

100% biodiesel absorbed 15 and 10 times more water respectively than diesel. Fregolente et al

[14] ultimately concluded that the soluble water content of biodiesel, diesel, and blends depends

strongly on the temperature and blend ratio. Blending creates a mixture with a lower capacity for

water absorption, while the addition of biodiesel in diesel increases the water holding capacity of

the blend. Also it was found that under a relative humidity of 79% and 66%, there was an

increase of 51% and 23% respectively, of water content for 100% biodiesel and an increase of

only 8% and 7% respectively, of water content for diesel samples.

Due to the inherent nature of biodiesel to absorb water, microbial contamination is a

serious problem as the presence of such organisms enhances corrosion via biocorrosion or MIC.

2.3 Biocorrosion/MIC

Biocorrosion, is a result of interactions, which are often synergistic, between the metal

surface, abiotic corrosion products, and bacterial cells and their metabolites [2]. A unifying

electron-transfer hypothesis offers MIC of ferrous metals as a model system for the study of

metal-microbe interactions. It states that biocorrosion is a process in which metabolic activities

of microorganisms associated with metallic materials supply insoluble products which are able to

accept electrons from the base metal. This sequence of biotic and abiotic reactions produces a

kinetically favored pathway of electron flow from the metal anode to the universal electron

acceptor, oxygen [4]. However, the hypothesis does not take into account the possibility that the

organic component of the biofilm matrix itself can facilitate electron transfer from the metal to

an electron acceptor such as oxygen. For example, enzymes active within the biofilm matrix and

metal ions bound by bacterial extracellular polymeric substances can catalyze cathodic reactions

[2]. Thus, it is important to take a closer look at the biofilm to understand its role in biocorrosion.

11

2.4 Biofilm

The development of the biofilm is facilitated by the production of extracellular polymeric

substances (EPS) comprising macromolecules such as proteins, polysaccharides, nucleic acids

and lipids [2]. Growth of the biofilm is considered to be the result of complex processes

involving the transport of organic and inorganic molecules and microbial cells to the surface,

adsorption of molecules to the surface, and initial attachment of microbial cells followed by their

irreversible adhesion facilitated by production of EPS, often referred to as the glycocalyx or

slime [15]. It has also been documented that degradation of metal surfaces occurs when the

contact between microbial cells, or products of their metabolism such as EPS, and the surface is

established [16].

The EPS plays an important role in attachment to metal surfaces. It also has the ability to

complex with metal ions [16]. This is important since for all bacteria to grow, metal ions are

required. The availability and type of ions are likely to have an effect on the colonization of a

metal surface [16].

2.5 Case Studies

The coupling of microorganisms to corrosion usually gives the adverse effect of

accelerated corrosion. MIC has posed to be a serious problem in biodiesel usage, storage, and

transportation. Here is a summary of notable studies documenting the extent of biocorrosion

damage to storage tanks and pipeline steel.

In 2010, Aktas et al [17] exposed biodiesel to anaerobic microorganisms from fresh water

and marine environments with differing histories of exposure to hydrocarbons, biodiesel, and

oxygen. Gas chromatography was used to measure biodegradation of biodiesel, while

electrochemical and imaging techniques was used to monitor corrosion of carbon steel over a 60

12

day period. A soy-based biodiesel was used in their experiments. A total of five different

anaerobic inocula were used as the microbial contaminant. The experiment was performed in

triplicate with environmental conditions stated as seawater immersion, seawater/biodiesel

interface, and biodiesel immersion. Two common features of the five diverse anaerobic inocula

were that they could reduce sulfate or produce methane in less than or equal to one month in

biodiesel-amended incubations, well in excess of biodiesel-free or sterile negative controls, and

that all inocula metabolized biodiesel, regardless of their freshwater or marine origins or prior

history to biodiesel, over a very short time period, from weeks to one month.

Another study performed in the same year designed experiments to evaluate the nature

and extent of microbial contamination and the potential for MIC in alternative fuels, i.e.,

biodiesel, ULSD, and blends of the two. The main objectives of this work was to characterize the

corrosion and electrochemical behavior of storage and fuel tank alloys in the presence of

alternative fuels over time, and to determine the microflora and chemistry of as-received fuels as

a function of biodiesel content and storage time [18]. ULSD, L100, B100, B5, and B20 were the

selected fuels for this experiment. Microorganisms were identified via denaturing gradient gel

electrophoresis, DGGE, and by 16S rRNA for bacteria and 28S rRNA for fungi. The selected

materials to represent fuel tank alloys were the following: carbon steel UNS C10200, stainless

steel UNS S30403, and aluminum alloy UNS A95052. To ensure microbial contamination within

the experiments, an inoculum was used from the sludge layer in a tank containing L100. After a

two week period, the water layer was separated from the sludge using a separation funnel. 20 mL

of this contaminated water was then added to each experimental fuel/water mixture which would

be exposed for a total duration of six months. Lee et al [18] found that for each fuel/water

combination, microorganism species diversity generally decreased over the six months. Stainless

13

steel exhibited no visual signs of corrosion. Visual and microscopic analyses revealed an absence

of corrosion on C1020 in the presence of biodiesel, even in the lowest concentration. Lee et al

[18] hypothesized that biodiesel has a passivating effect on C1020. In the case of aluminum,

pitting was visually observed in all AA5052 fuel/water exposures. Overall, Lee et al [18]

concluded that C1020 exhibited general active corrosion in ULSD and L100, and passive

behavior in B100 and biodiesel/ULSD blends. SS304L remained passive in all exposures, and

AA5052 was susceptible to subsurface pitting in the water and fuel layers, in addition to the

fuel/water interface.

14

Chapter 3

Materials and Methods

3.1. Introduction

This section describes the materials and methods used for the biodiesel experiments.

3.2. Materials Used

Plain carbon 1018 steel was chosen as the material to be investigated based on its similar

chemical compositions to that of ASTM A36 steel and API Spec 5L X60, which are often used

for fuel tank storage and pipelines, respectively. Table 1 tabulates the chemical compositions of

these specifications and 1018 grade steel.

Table 1. Chemical composition of selected specifications and 1018 steel.

Material Specifications

Chemical Composition C, max. % Mn, max. % P, max. % S, max. %

ASTM A36 0.25 - 0.04 0.05 API Spec 5L X60 0.28 1.40 0.03 0.03

Material Chemical Composition C, % Mn, % P, max. % S, max. %

1018 Steel 0.15 - 0.20 0.60 - 0.90 0.035 0.04

The types of fuel that was chosen for this experiment were 100% biodiesel (B100), 20%

biodiesel (B20), and ultra-low sulfur diesel (ULSD) for control. These fuels were obtained

locally from gas stations (i.e., 76 and Aloha Petroleum gas stations). To further investigate the

effects of biodiesel on corrosion, a second set consisting of sterilized versions of the

aforementioned fuels were used. Sterility of the B100, B20, and ULSD fuels were achieved via

vacuum filter sterilization by a 0.22 µm Millipore membrane filter.

15

3.3. Experimental Setup

The 1018 steel coupons were machined to the following dimensions: 2.25 in. x 1 in. x

0.125 in. A BenchMark 320 marking system was used to pin stamp the coupons for identification.

The coupons were then acetone washed to remove any oil residue and weighed to obtain an

initial mass. To prevent oxidation of the steel, the coupons were kept in a dry box (< 1% relative

humidity) prior to the experiment.

Nanopure water was added to facilitate contamination within the fuels. This fuel-water

mixture (40 mL fuel, 40 mL water) was stored in 100 mL glass Pyrex media bottles. The 1018

steel coupon samples were placed in these fuel-water mixtures at an approximate angle of 45°

with respect to the horizon. Figure 1 depicts this setup.

Figure 1. Experimental setup of fuel-water mixtures with 1018 steel coupons immersed. Left to

right: B100/water mixture, B20/water mixture, and ULSD/water mixture.

Triplicates of each fuel-water mixture and 1018 steel coupon were exposed outdoors

under the three following environmental conditions: anaerobic, aerobic, and selective aerobic.

UV exposure from the sun and rain water contamination was kept to a minimum by encasing

16

samples in boxes under a protective alcove. The following figure depicts the environmental

systems.

Figure 2. B100/water fuel mixture depicting anaerobic, aerobic, and selective aerobic

environments. Anaerobic cap and selective aerobic cap depicted. Bottles with an orange cap are sealed air-tight to simulate an anaerobic environment.

Uncapped bottles simulate an aerobic environment, while bottles with a gray cap simulate a

“sterile” aerobic environment. The gray cap is fitted with a 0.22 µm filter at the top to allow only

air to be exchanged into and out of the bottle. Contamination from the outside environment will

not be able to enter the bottle.

An exposure time of 6 months and 1 year were chosen for this experiment to compare

and contrast the corrosion of the steel samples.

The following table summarizes the entire experimental design.

Table 2. Experimental design. Fuel Environment Exposure TimeB100 Anaerobic 6 Months B20 Aerobic 1 Year ULSD Selective Aerobic Sterile B100 Sterile B20 Sterile ULSD

0.22 µm filter

17

Therefore, since the experiment was run in triplicate, a total of 108 samples were exposed under

these conditions. The following figure depicts the entire experimental setup and deployment.

Figure 3. 108 samples loaded in boxes to be exposed outdoors for six months and one year.

3.4. pH Measurements

pH measurements were taken of both water and fuel layers within samples. The pH was

determined using a Thermo Scientific Orion gel-filled pH/ATC triode with epoxy body electrode

connected to a Thermo Scientific Orion 4-star pH/RDO portable meter as depicted by Figure 4.

Prior to taking measurements, a two buffer calibration procedure was performed to ensure

accuracy. Since the predicted pH measurements were assumed to be more acidic than alkaline,

buffers of pH 4 and 7 were used in this calibration process.

18

Figure 4. pH measurement setup.

3.5. Dissolved Oxygen (DO) Measurements

DO measurements were taken to determine how quickly oxygen was depleted from the

three environmental conditions. DO readings were taken every 5 minutes for a duration of 1 hour

using a Thermo Scientific field RDO probe connected to a Thermo Scientific Orion 4-star

pH/RDO portable meter as depicted by Figure 5.

Figure 5. DO experimental setup.

19

3.6. Total Acid Number Measurements

TAN is essentially defined as the number of milligrams of KOH required to neutralize the

acidity in one gram of oil [19]. Therefore, oil with high TAN values, approximately > 0.5, are

less desirable since they have been known to cause problems with respect to corrosion and

refinery processes [19].

Individual Dexsil Titra-Lube TAN kits as depicted by Figure 6 were used to determine

the change in TAN of the fuels. These readings were taken upon receiving the fuels and upon

completion of both exposure time periods of 6 months and 1 year.

Figure 6. Dexsil TAN kit.

3.7. Microbial Contamination

A preliminary 1 month experiment was conducted to assess microbial contamination

within B100 fuels. Blood agar plates which consist of tryptic soy agar with an addition of 5%

defibrinated sheep blood was used as the microbial media to culture microorganisms within the

B100 fuel. Blood agar plates are a general purpose media used to encourage growth of more

fastidious microorganisms [20]. 100 μl samples of B100 fuels were pipetted onto blood agar

plates and incubated aerobically for a maximum of 1 week at 35°C. Unfortunately, no

microorganisms could be cultured directly from the fuel. Literature suggests that microorganism

20

contamination only occurs with the introduction of water into the fuel [5]. Therefore, a B100

fuel-water mixture consisting of 10 mL of B100 fuel and 10 mL of deionized water was exposed

outdoors aerobically for 1 month in 100 mL Pyrex media bottles. After the 1 month exposure,

100 μl of the water layer in the B100 fuel-water mixture was plated on blood agar plates and

incubated as described previously. The following figures depict the isolated bacteria colonies

cultured in the laboratory from this preliminary experiment along with their species specific

molecular identification.

Figure 7. Bacteria sample, 16S rRNA sequencing yields a 65% match to the bacterial species

Bacillus licheniformis.

21


Aeromicrobium tamlense.


Bacillus horikoshi.

22


Bacillus novalis.

Upon isolation of these microorganisms, colony polymerase chain reaction (PCR) was

carried out according to Suzuki et al [21] using a thermal cycler depicted by Figure 11. The

products of the PCR were sent to be sequenced at Greenwood Molecular Biology Facility located

on the University of Hawaii at Manoa campus. Upon successful sequencing of the PCR products,

species specific bacteria identification was possible using a BLAST search database.

All fuel samples used in this experiment underwent similar microbial screening for

contamination. Existing microorganisms within fuels were determined by plating 100 μl samples

of fuels on blood agar and tryptic soy agar plates. Tryptic soy agar plates were used since it is

considered a standard media in microbiology [20]. Plates were incubated in an aerobic incubator

set to 26°C and monitored for 1 week.

Upon sample retrieval of the 6 month exposure and 1 year exposure times, another

sampling of fuels, fuel-water layer interface, and water were carried out. Again, 100 μl of fuel,

fuel-water layer, and water from samples were plated on blood agar, tryptic soy agar, and an

23

additional type of media, R2A. Samples were incubated for 1 week in an aerobic and anaerobic

incubator for 1 week at a temperature of 26°C.

Microbial contamination was then down-processed via molecular biology techniques

such as polymerase chain reaction and genetic sequencing to identify up to the species level of

microorganisms as previously performed in the preliminary microbial contamination experiment.

Figure 11. Eppendorf thermo cycler.

3.8. Corrosion Product Characterization – Raman Spectroscopy

Characterization of corrosion product via Raman spectroscopy was performed similarly

to Li et al [22]. A Nicolet Almega XR dispersive Raman Spectrometer (Thermo Scientific Corp.)

equipped with multiple Olympus objectives and a Peltier-cold charge-coupled device (CCD)

detector was used for the experiments. An objective with magnification of 50× with estimated

24

spatial resolutions of 1.6 μm was used. The instrument was operated with laser sources of a

green Nd:YAG laser with 532 nm wavelength excitation and an infrared diode laser with 780 nm

wavelength excitation.

The maximum spectra resolution was up to 2.2 – 2.6 cm-1 using a 25 μm pinhole or slit,

which requires longer acquisition time and produces more noise. To reduce the collecting time,

an aperture of 100 μm pinhole was used, giving an estimated resolution in the range of 8.4 – 10.2

cm-1. The accumulation time was 120 seconds.

Figure 12. Raman spectroscopy setup.

3.9. Corrosion Product Characterization – Scanning Electron Microscope (SEM)

A Hitachi S-3400N SEM equipped with an Oxford Instruments energy dispersive X-ray

analyzer system was used to characterize the 1018 steel coupons. Quantitative elemental analysis

(fixed-point) was conducted on corroded regions on sample steel coupons.

25

Figure 13. SEM/EDXA setup.

3.10. Corrosion Product Characterization – X-Ray Diffraction (XRD) A Rigaku MiniFlex™ II benchtop XRD system equipped with a Cu (Kα) radiation was

used for XRD measurements. X-ray diffraction spectra were obtained directly on the corroded

steel coupon surfaces. The scans were done in the range of 3 – 90° (2(θ)). A scan speed of 1°

(2θ)/min was used.

Figure 14. XRD analysis setup.

26

3.11. Weight Loss Technique

The penetration rate (mm/year) was calculated for each steel coupon based on the total

mass loss. The following equation was used to calculate the penetration rate for steel coupon

samples:

ρ1x

tAmRatenPenetratio⋅

Δ=

where Δm is the change in mass in grams, A the area of the sample in mm2, t the time in years,

and ρ the density of the 1018 steel in g/mm3.

To obtain the total mass loss, the steel coupons were cleaned with an acid wash to

remove any corrosion product. The acid wash procedure followed ISO 8407 – “Removal of

corrosion products from corrosion test specimens.” After acid washing and air drying, the steel

coupons were weighed and compared to their respective initial mass values to obtain the total

mass loss.

27

Chapter 4

Thermodynamics of Iron

To determine thermodynamically whether iron will have the tendency to corrode in an

aerated fuel-water solution of pH (0, 1, 2, 3, 4, 5, 6, and 7) at 30ºC, the following calculations

were made.

The following represent the anodic reaction or the oxidation of iron, and the cathodic

reaction or the reduction of oxygen. Their respective standard potentials, Φ° , are given,

measured in volts with respective to the standard hydrogen electrode.

Fe → Fe2+ + 2e- (Φ°= -0.440 VSHE)

O2 + 2H2O + 4e- → 4OH- (Φ°= 0.401 VSHE)

Balancing these two reactions yields the following overall reaction:

2Fe → 2Fe2+ + 4e- O2 + 2H2O + 4e- → 4OH-

2Fe + O2 + 2H2O → 2Fe2+ + 4OH-

The overall electrochemical cell potential of the cell is defined by the following equation below:

FeFeOHOcellE// 2

2+− −= φφ

where −OHO /2

φ is the equilibrium or reversible potential for the cathodic reaction, and FeFe /2+φ is

the equilibrium or reversible potential for the anodic reaction. −OHO /2φ can also be re-written in

the form of the Nernst Equation which follows below:

28

2

4

// ))(()(

log303.2

2222

OHO

OHOHOOHO aa

anF

RT −

−− −°= φφ

where −°

OHO /2φ is defined as the equilibrium or reversible standard state potential, R the

universal gas constant, 8.314 J/K•mol, T, the temperature in K, n, the number of electrons, F,

Faraday’s constant, 96,487 C/mol, and −OHa ,

2Oa , OHa2

, the respective activities. The activities

are calculated as follows below:

pHOH

pHH

HOH

a

a

aa

−

−

−

−

=

=

=×

−

+

+−

1010

10

10

14

14

For the activity −OH

a , it can be shown from above that −OHa is related to the pH. In the case for

activity 2Oa , as shown below, the activity is related to the partial pressure of oxygen which

accounts for roughly 20% of air.

2.012.0

1

2

2

2

==

=

atmatma

atmP

a

O

OO

Lastly, the activity OHa

2 is simply equal to 1 since water is a one component heterogeneous

phase.

12=OHa

Thus, the following table tabulates the equilibrium potential −°

OHO /2φ for varying pH values.

29

Table 3. Equilibrium potential of −°OHO /2

φ for various pH values.

pH −OHO /2φ (VSHE)

0 1.2323 1 1.1722 2 1.1120 3 1.0519 4 0.9918 5 0.9316 6 0.8715 7 0.8114

Similarly, the equilibrium or reversible potential for the anodic reaction,

FeFe /2+φ , can also

be re-written in the form of the Nernst Equation which follows below:

2

2

// )()(log303.2

2

22

+

++ −°=Fe

FeFeFeFeFe a

anF

RTφφ

Again,

FeFe /2+°φ is defined as the equilibrium or reversible standard state potential, R the


Faraday’s constant, 96,487 C/mol, and Fea , +2Fea , the respective activities. The activities are

calculated as follows below:

1=Fea The activity Fea shown above is equal to 1 since iron is a one component heterogeneous phase.

For the activity +2Fea , more detailed calculations are required as depicted below.

2)(2

−

+ =OH

spFe a

Ka

For iron(II) hydroxide, Fe(OH)2, the reaction and solubility product, spK , is given below.

Fe(OH)2 → Fe2+ + 2OH-

16108 −×=spK

30

Therefore the activity +2Fea can be solved by the following:

162 108)(2

−×=× −+ OHFeaa

where the activity −OH

a , is calculated as before.

pHOHa −

−

=− 1010 14

Hence, the following table tabulates the equilibrium potential

FeFe /2+°φ for varying pH values. Table 4. Equilibrium potential of

FeFe /2+°φ for various pH values. pH

FeFe /2+φ (VSHE) 0 -0.0521 1 -0.1122 2 -0.1723 3 -0.2325 4 -0.2926 5 -0.3527 6 -0.4128 7 -0.4730

Now the overall electrochemical cell potential can be calculated.

FeFeOHOcellE

// 22

+− −= φφ

The table below tabulates the overall electrochemical cell potential. Table 5. Overall electrochemical cell potential for various pH values.

pH −OHO /2φ (VSHE)

FeFe /2+φ (VSHE) cellE (V)

0 1.2323 -0.0521 1.2844 1 1.1722 -0.1122 1.2844 2 1.1120 -0.1723 1.2843 3 1.0519 -0.2325 1.2844 4 0.9918 -0.2926 1.2844 5 0.9316 -0.3527 1.2843 6 0.8715 -0.4128 1.2843 7 0.8114 -0.4730 1.2844

Therefore, since Ecell > 0 in all cases, the reaction is spontaneous to the right and iron has the

tendency to corrode in the system.

31

Similarly, to determine thermodynamically whether iron will have the tendency to

corrode in a deaerated fuel-water solution of pH (0, 1, 2, 3, 4, 5, 6, and 7) at 30ºC, the following

calculations were carried out below.

The following represent the anodic reaction or the oxidation of iron, and the cathodic

reaction or the evolution of hydrogen. Their respective standard potentials, Φ°, are given,

measured in volts with respective to the standard hydrogen electrode.

Fe → Fe2+ + 2e- (Φ° = -0.440 VSHE)

2H+ + 2e- → H2 (Φ° = 0 VSHE)

Balancing these two reactions yields the following overall reaction:

Fe → Fe2+ + 2e-

2H+ + 2e- → H2

Fe + 2H+ → Fe2+ + H2 The overall electrochemical cell potential of the cell is defined by the following equation below:

FeFeHHcellE// 2

2++ −= φφ

where

2/ HH +φ is the equilibrium or reversible potential for the cathodic reaction, and FeFe /2+φ is

the equilibrium or reversible potential for the anodic reaction. 2/ HH +φ can also be re-written in the

form of the Nernst Equation which follows below:

2// )(log303.2 2

22+

++ −°=H

HHHHH a

anF

RTφφ

where

2/ HH +φ is defined as the equilibrium or reversible standard state potential, R the universal

gas constant, 8.314 J/K•mol, T, the temperature in K, n, the number of electrons, F, Faraday’s

32

constant, 96,487 C/mol, and 2Ha , +H

a , the respective activities. The activities are calculated as

follows below:

6

6

101

101

2

2

2

2

−

−

=

=

=

H

H

HH

aatm

atma

atmP

a

For the activity

2Ha , it can be shown from above that 2Ha is related to the partial pressure of

hydrogen which accounts for roughly 0.6 ppm of air. In the case for activity +Ha , as shown

below, the activity is related to pH.

pH

Ha −=+ 10

Thus, the following table tabulates the equilibrium potential

2/ HH +φ for varying pH values.


2/ HH +φ for various pH values.

pH 2/ HH +φ (VSHE)

0 0.1804 1 0.1203 2 0.0601 3 0.0000 4 -0.0601 5 -0.1203 6 -0.1804 7 -0.2405

Similarly, the equilibrium or reversible potential for the anodic reaction,

FeFe /2+φ , can also

be re-written in the form of the Nernst Equation which follows below:

+

++ −°=2

22 log303.2//

Fe

FeFeFeFeFe a

anF

RTφφ

33

Again, FeFe /2+°φ is defined as the equilibrium or reversible standard state potential, R the


Faraday’s constant, 96,487 C/mol, and Fea , +2Fea , the respective activities. The activities are

calculated in the same way as in the aerated case above. Hence, the following table tabulates the

equilibrium potential FeFe /2+°φ for varying pH values.


FeFe /2+°φ for various pH values. pH

FeFe /2+φ (VSHE) 0 -0.0521 1 -0.1122 2 -0.1723 3 -0.2325 4 -0.2926 5 -0.3527 6 -0.4128 7 -0.4730

Now the overall electrochemical cell potential can be calculated.

FeFeHHcellE

// 22

++ −= φφ

The table below tabulates the overall electrochemical cell potential. Table 8. Overall electrochemical cell potential for various pH values.

pH 2/ HH +φ (VSHE) FeFe /2+φ (VSHE) cellE (V)

0 0.1804 -0.0521 0.2325 1 0.1203 -0.1122 0.2325 2 0.0601 -0.1723 0.2324 3 0.0000 -0.2325 0.2325 4 -0.0601 -0.2926 0.2325 5 -0.1203 -0.3527 0.2324 6 -0.1804 -0.4128 0.2324 7 -0.2405 -0.4730 0.2325

Similar to the aerated case, since Ecell > 0 in all cases, the reaction is spontaneous to the right and

iron has the tendency to corrode in the system.

34

These calculations serve to verify that iron will have the tendency to corrode regardless

of oxygen levels within the environment since the environmental conditions of the experiment

will consist of both anaerobic and aerobic settings.

35

Chapter 5

Corrosion Product Characterization

5.1. Introduction

This section summarizes the characterization of corrosion product found on sample steel

coupons. Techniques such as Raman spectroscopy, XRD, and SEM/EDXA were used to

characterize and determine any trends found in corrosion product.

5.2. Corrosion Product Morphology

A Nikon D700 DSLR camera equipped with AF Micro-NIKKOR 60mm f/2.8D was used

to obtain images of sample coupons. The figures below depict the 6 month and 1 year steel

coupons retrieved from specified environments. All steel coupons immersed in filtered and

unfiltered B100 and B20 fuels were lightly acetone washed to remove oil residue prior to digital

imaging. Steel coupons immersed in filtered and unfiltered ULSD did not have to be acetone

washed as very little oil residue remained upon retrieval of coupons.

36

6 Month Steel Coupon Samples Exposed in Anaerobic Environment B100 Unfiltered B100 Filtered

B20 Unfiltered B20 Filtered

ULSD Unfiltered ULSD Filtered

Figure 15. 6 month steel coupon samples exposed in an anaerobic environment segregated by

type of fuel.

37

6 Month Steel Coupon Samples Exposed in Aerobic Environment B100 Unfiltered B100 Filtered



Figure 16. 6 month steel coupon samples exposed in an aerobic environment segregated by type

of fuel.

38

6 Month Steel Coupon Samples Exposed in Selective Aerobic Environment B100 Unfiltered B100 Filtered



Figure 17. 6 month steel coupon samples exposed in a selective aerobic environment segregated

by type of fuel.

39

1 Year Steel Coupon Samples Exposed in Anaerobic Environment B100 Unfiltered B100 Filtered



Figure 18. 1 year steel coupon samples exposed in an anaerobic environment segregated by type

of fuel.

40

1 Year Steel Coupon Samples Exposed in Aerobic Environment B100 Unfiltered B100 Filtered



Figure 19. 1 year steel coupon samples exposed in an aerobic environment segregated by type of

fuel.

41

1 Year Steel Coupon Samples Exposed in Selective Aerobic Environment B100 Unfiltered B100 Filtered



Figure 20. 1 year steel coupon samples exposed in a selective aerobic environment segregated by

type of fuel.

42

These figures reveal trends on corrosion product deposition specific to location. For

example, 6 month exposure steel coupons exposed in filtered and unfiltered B100 fuel-water

mixtures exhibited corrosion product on the top part, or fuel layer, and interface of the coupon as

depicted by Figures 15, 16, and 17. Corrosion product on the lower part, or water layer, of the

coupons are non-existent or very sparse with the exception of some such as the steel coupons

immersed in filtered B100 fuel-water mixtures exposed in a selective aerobic environment as

depicted by Figure 17. In contrast, steel coupons exposed in B20 or ULSD fuel-water mixtures

exhibit corrosion product primarily on the lower part, or water layer, of the coupon as depicted

by Figures 15, 16, and 17. For the case of steel coupons immersed in filtered and unfiltered B20

fuel-water mixtures exposed in an aerobic environment, virtually no corrosion product was found

as depicted by Figure 16. The steel coupons immersed in the filtered and unfiltered ULSD fuel-

water mixtures exposed in an aerobic environment visually exhibited the worst corrosion as both

top and bottom parts of the steel coupons were corroded as depicted by Figure 16.

For the 1 year exposure time period, steel coupons exposed in filtered and unfiltered

B100 and B20 fuel-water mixtures exhibited very little corrosion product, with most, if any,

located on the top part of the coupons as depicted by Figures 18, 19, and 20. Steel coupons

immersed in filtered and unfiltered ULSD fuel-water mixtures followed the same trends as their

6 month exposure steel coupon counterparts as depicted by Figures 18, 19, and 20.

Microbial evidence was revealed only on steel coupons exposed to both filtered and

unfiltered B20 fuel-water mixtures exposed in an aerobic environment. This was true for both 6

month and 1 year exposures.

43

Figure 21. Microbial contamination in the form of sludge on 1018 steel coupon exposed in

filtered/unfiltered B20 fuel-water mixture in aerobic environment.

The sludge layer of the steel coupon as depicted by Figure 21 is visual evidence of microbial

activity as suggested by literature [5, 14, 18].

44

5.3. Raman Spectroscopy The following figures depict the results obtained via Raman spectroscopy for the 6 month

exposure time period. The y-axis for all Raman results is an arbitrary intensity value, whereas the

x-axis is the more important Raman shift in cm-1 which reveals the band locations of corrosion

products.

Figure 22. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered B100 fuel samples in anaerobic (1UC61), selective aerobic (1UM63), and aerobic (1UO61) environments.

Characteristic bands of lepidocrocite (250.92, 395.79, 307.67, 370.55, 308.63, and 383.41

cm-1) [22] were observed for all steel coupons in Figure 22. Other bands (222.70, 535.96, 225.41,

276.72, 531.66, 225.54, 281.85, and 521.52 cm-1) [22] in the figure are ghost bands obtained

using the 780 nm laser system. Unfortunately, bands 468.56 and 422.68 cm-1 could not be

45

identified. In further analysis via XRD, corrosion product of iron formate hydrate is found. Thus,

perhaps these bands belong to that corrosion product. Literature reveals no information regarding

Raman band locations of this type of corrosion product.

Figure 23. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered B100 fuel samples in anaerobic (1FC63), selective aerobic (1FM63), and aerobic (1FO62) environments.

Characteristic bands of lepidocrocite (246.06, 304.90, 343.38, 373.98, 636.88, 246.19,

301.98, 341.35, 372.51, 641.96, and 218.75 cm-1) [22] were observed for all steel coupons in

Figure 23. Again, the remaining bands (221.91, 521.04, 225.56, and 521.05 cm-1) [22] are ghost

bands.

46

Figure 24. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered B20 fuel

samples in anaerobic (2UC62) and selective aerobic (2UM63) environments.

1018 steel coupon 2UC62 has two spectrum obtained via Raman due to different

corrosion product morphology sites (orange and black) on the coupon. Characteristic bands of

lepidocrocite (247.17, 304.33, 344.85, 372.98, 214.06, 241.52, 302.45, and 389.60 cm-1) [22] and

magnetite (644.41, 652.65, and 668.72 cm-1) [22] were observed as depicted in Figure 24.

Remaining bands (220.43, 524.65, 228.01, 220.36, 223.45, 282.00, and 526.06 cm-1) [22] were

identified as ghost bands. Although Raman measurements were taken at two different sites on

steel coupon 2UC62, both corrosion products of lepidocrocite and magnetite were observed. This

is due to the observation that lepidocrocite seems to form over magnetite and vice versa. Hence,

as the laser penetrates the sample, both corrosion products are detected. Lepidocrocite was the

only corrosion product found on steel coupon 2UM63. Raman data is missing for steel coupons

47

exposed in unfiltered B20 fuel-water mixtures placed in aerobic environments since no corrosion

product was detected upon acetone washing the sludge layer off the coupons.

Figure 25. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered B20 fuel

samples in anaerobic (2FC63) and selective aerobic (2FM61) environments.

Similar to the 1018 steel coupons exposed in unfiltered B20 fuel-water mixtures of

Figure 24, lepidocrocite (245.89, 298.66, 343.70, 372.42, 285.53, 390.80, 245.99, 303.44, 341.53,

and 372.74 cm-1) [22] and magnetite (641.92, 641.35, and 644.43 cm-1) [22] corrosion product

bands were observed as depicted by Figure 25. Other bands (220.02, 525.24, 222.37, 520.94,

225.11, 524.52, 209.96, and 220.90 cm-1) [22] are ghost bands. Steel coupons 2FC63 and 2FM61

exhibited similar corrosion product morphology as steel coupon 2UC62 from Figure 24.

Analysis from XRD reveals that steel coupon 2FM61 black should have magnetite corrosion

product present, but, magnetite bands were missing from the Raman spectra. Again, Raman data

is missing for steel coupons exposed in filtered B20 fuel-water mixtures placed in aerobic

48

environments since no corrosion product was detected upon acetone washing the sludge layer off

the coupons.

Figure 26. Raman spectroscopy of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel

samples in anaerobic (3UC61 and 3UC63) environments.

Characteristic bands of lepidocrocite (316.80, 244.24, 294.05, and 372.56 cm-1) [22] and

magnetite (659.86 cm-1) [22] were observed as depicted by Figure 26. The remaining bands

(231.61, 521.65, 224.77, 524.69, 171.96, 199.39, 224.73, and 528.54 cm-1) [22] are ghost bands.

Two different corrosion product morphologies were observed on 1018 steel coupons exposed in

unfiltered ULSD fuel-water mixtures placed in anaerobic environments. The first, 3UC61,

appeared to exhibit only the corrosion product magnetite, while the other coupon, 3UC63,

depicted corrosion product morphologies similar to the B20 fuel-water mixture steel coupons

2UC62, 2FC63, and 2FM61 of Figure 25. Steel coupon 3UC61 revealed both lepidocrocite and

49

magnetite as corrosion products whereas steel coupons 3UC63 orange and 3UC63 black revealed

only lepidocrocite and no corrosion product, respectively.

Figure 27. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered ULSD fuel

samples in anaerobic (3FC61 and 3FC63) environments.

Characteristic bands of lepidocrocite (248.27, 305.79, and 374.71 cm-1) [22] and

magnetite (658.87 cm-1) [22] were observed as depicted by Figure 27. The remaining bands

(144.12, 227.03, 224.91 and 524.65 cm-1) [22] are ghost bands. Again, two different corrosion

product morphologies were observed on 1018 steel coupons exposed this time in filtered ULSD

fuel-water mixtures placed in anaerobic environments. The first, 3FC61 appeared to exhibit only

the corrosion product magnetite while the other coupon, 3FC63 depicted corrosion product

morphologies similar to the B20 fuel-water mixture steel samples 2UC62, 2FC63, 2FM61 and

ULSD fuel-water mixture sample coupon 3UC63 of Figures 24 and 26 respectively. However,

Raman measurements detected no corrosion product spectrum for the 3FC61 coupon with only

50

two ghost bands detected. Again, magnetite is the suspect corrosion product, but the Raman was

unable to detect its presence. Steel coupon 3FC63 exhibited both lepidocrocite and magnetite as

corrosion products.

Figure 28. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered and unfiltered ULSD fuel samples in selective aerobic (3FM63 and 3UM61) environments.

Characteristic bands of lepidocrocite (219.30, 375.15, and 222.30 cm-1) [22] and goethite

(248.62 and 246.87 cm-1) [22] were observed for all steel coupons in Figure 28. The remaining

bands (225.54, 525.81, 225.80, and 532.26 cm-1) [22] are ghost bands.

51

Figure 29. Raman spectroscopy of 6 months 1018 steel coupons exposed in filtered and

unfiltered ULSD fuel samples in aerobic (3FO63 and 3UO61) environments.

Similarly, for the case of 1018 steel coupons immersed in ULSD fuel-water mixtures

exposed in an aerobic environment, characteristic bands of lepidocrocite (371.94, 305.09, 246.91,

and 374.37 cm-1) [22] and goethite (247.84, 246.91, and 384.45 cm-1) [22] were observed as

depicted by Figure 29. The remaining bands (224.98, 518.51, 224.85, 525.05, 225.63, and 524.80

cm-1) [22] are ghost bands. For steel coupon 3UO61, two different corrosion product

morphologies were observed. The top part of the coupon exhibited both lepidocrocite and

goethite whereas the bottom part revealed only lepidocrocite. This is quite different when

compared to its filtered counterpart, steel coupon 3FO63 which exhibited both lepidocrocite and

goethite on the bottom part of the coupon.

52

Similarly, the following figures depict the results obtained via Raman spectroscopy for

the 1 year exposure time period.

Figure 30. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered and unfiltered

B100 fuel samples in anaerobic (1FC13 and 1UC12) environments.

Very faint bands, characteristic of lepidocrocite (381.84 and 367.10 cm-1) [22] were

observed for both steel coupons in Figure 30. The remaining bands (221.79, 527.46, 224.54, and

533.55 cm-1) [22] are ghost bands.

53


B100 fuel samples in selective aerobic (1FM12 and 1UM11) environments.

Characteristic bands of lepidocrocite (294.94, 390.75, and 367.32 cm-1) [22] were

observed as depicted by Figure 31. Remaining bands (224.71, 529.34, 225.69, 525.86, and

221.24 cm-1) [22] are ghost bands. Corrosion product was especially sparse on steel coupon

1UM11 which is why the Raman could not detect any bands.

54

Figure 32. Raman spectroscopy of 1 year 1018 steel coupons exposed in unfiltered B100 fuel

samples in an aerobic (1UO12) environment.

One band characteristic of lepidocrocite (316.86 cm-1) [22] was observed on the 1UO12

orange steel coupon. Other bands (222.11, 221.41, 526.90, and 222.85 cm-1) [22] are ghost bands.

Bands at 426.91, 426.16, 581.06, and 561.11 cm-1 unfortunately could not be identified. Similar

to the case of Raman results for the 6 month time period exposure of Figure 22, these

unidentified bands may belong to the corrosion product iron formate hydrate as XRD analysis

confirms this type of product on the steel coupons.

55

Figure 33. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered B100 fuel

samples in an aerobic (1FO12) environment.

Characteristic bands of lepidocrocite (305.72 and 388.65 cm-1) [22] and maghemite

(463.73 cm-1) [22] were observed as depicted by Figure 33. Remaining bands (220.74, 523.59,

224.39, 521.20, 220.23, and 286.91 cm-1) [22] are ghost bands. Band 577.55 cm-1 could again not

be identified. Steel coupon 1FO12 orange revealed lepidocrocite and maghemite, which has the

same structure of magnetite, as corrosion products. No spectrum was detected at the interface

region of steel coupon 1FO12. This is likely due to the very little corrosion product observed in

that area.

56

Figure 34. Raman spectroscopy of 1 year 1018 steel coupons exposed in unfiltered B20 fuel

samples in anaerobic (2UC12) and selective aerobic (2UM11) environments.

Characteristic bands of lepidocrocite (308.77, 366.89, 220.96, and 373.05 cm-1) [22] were

observed as depicted by Figure 34. Remaining bands (224.58, 531.04, 226.12, 527.60, 225.01,

and 529.73 cm-1) [22] are ghost bands. Steel coupons 2UC12 and 2UM11 both revealed

lepidocrocite as the corrosion product. Again, the interface for steel coupon 2UM11 had very

little corrosion product and therefore no Raman spectrum could be obtained. Similar to the 6

month steel coupon samples exposed in an aerobic environment, Raman data is missing since no

corrosion product was detected upon acetone washing the sludge layer off the coupons.

57

Figure 35. Raman spectroscopy of 1 year 1018 steel coupons exposed in filtered B20 fuel

samples in anaerobic (2FC13) and selective aerobic (2FM13) environments.

Lepidocrocite bands (245.32, 301.27, 344.73, and 371.93 cm-1) [22] were observed on

steel coupon sample 2FC13. Other bands (225.45, 523.73, 225.39, 525.80, 225.21, and 534.08

cm-1) [22] were identified as ghost bands. Band 580.20 cm-1 on steel coupon sample 2FM13

could not be identified. The interface for steel coupon 2FM13 had very little corrosion product

and therefore no Raman spectrum could be obtained. Again, Raman data is missing for steel

coupons exposed in the filtered B20 fuel-water mixtures placed in aerobic environments since no

corrosion product was detected upon acetone washing the sludge layer off the coupons.

58


ULSD fuel samples in anaerobic (3FC13, 3FC11, and 3UC11) environments.


302.60, and 371.17 cm-1) [22] and magnetite (597.51 and 654.11 cm-1) [22] were observed as

depicted by Figure 36. Remaining bands (225.50, 523.53, 281.72, 225.65, 525.95, 224.94,

266.52, and 515.93 cm-1) [22] were identified as ghost bands. Lepidocrocite was found only on

steel coupons 3FC13 and 3FC11. Magnetite was found only on the top part of steel coupon

3FC11 and the bottom of 3UC11.

59


ULSD fuel samples in selective aerobic (3FM13 and 3UM11) environments.

Characteristic bands of lepidocrocite (219.34, 490.25, 245.44, 301.46, 342.23, and 373.30

cm-1) [22] were observed in both steel coupons 3FM13 and 3UM11 as depicted by Figure 37.

The other remaining bands (266.51, 524.93, 225.44, and 522.13 cm-1) [22] are ghost bands.

60


ULSD fuel samples in aerobic (3FO12 and 3UO11) environments.


307.48, 340.79, and 376.00 cm-1) [22], goethite (248.60, 401.78, 489.50, and 543.24 cm-1) [22],

magnetite (604.39 cm-1) [22], and maghemite (445.12 cm-1) [22] were observed as depicted by

Figure 38. Remaining bands (225.38, 231.15, 286.47, 522.24, 277.56, 524.88, and 525.41 cm-1)

[22] were identified as ghost bands. Lepidocrocite was found on steel coupon 3FO12 and the

bottom part of steel coupon 3UO11. Goethite was found throughout steel coupon 3FO12.

Magnetite was found on the top part of steel coupon 3FO12, and maghemite was found on the

bottom part of steel coupon 3FO12.

61

5.4. XRD

The following figures depict the results obtained via XRD for the 6 month exposure time

period.

Figure 39. XRD of 6 months 1018 steel coupons exposed in unfiltered B100 fuel samples in

anaerobic (1UC61), selective aerobic (1UM63), and aerobic (1UO61) environments.

XRD results of Figure 39 reveal iron formate hydrate as the main corrosion product on

1018 steel coupons immersed in unfiltered B100 fuel-water mixtures exposed in all

environmental conditions. Raman analysis from Figure 22 agrees with XRD results and revealed

62

bands characteristic of lepidocrocite and two unknown bands that could possibly belong to iron

formate hydrate.

Figure 40. XRD of 6 months 1018 steel coupons exposed in filtered B100 fuel samples in

anaerobic (1FC63), selective aerobic (1FM63), and aerobic (1FO62) environments.

Lepidocrocite was identified by XRD analysis on steel coupons 1FC63 and 1FM63 as

depicted by Figure 40. No corrosion product was detected on steel coupon 1FO62. This

correlates well with Raman analysis of Figure 23, as lepidocrocite was identified as the primary

corrosion product on these steel coupons.

63

Figure 41. XRD of 6 months 1018 steel coupons exposed in unfiltered B20 fuel samples in

anaerobic (2UC62) and selective aerobic (2UM63) environments.

Lepidocrocite and magnetite was found on steel coupon 2UC62 whereas iron formate

hydrate was found on steel coupon 2UM63 as depicted by Figure 41. Raman analysis from

Figure 24 correlates well with steel coupon 2UC62 as both lepidocrocite and magnetite bands

were observed. In the case of steel coupon 2UM63, Raman analysis revealed lepidocrocite bands.

As for the case of the previous analysis performed with Raman, there is no XRD data for the

steel coupon samples exposed in the aerobic environement since no corrosion product was

detected upon acetone washing the sludge layer off the coupons.

64

Figure 42. XRD of 6 months 1018 steel coupons exposed in filtered B20 fuel samples in

anaerobic (2FC63) and selective aerobic (2FM61) environments.

Lepidocrocite and magnetite were found on both steel coupon samples 2FC63 and

2FM61 as depicted by Figure 42. Again, this correlates very well with Raman analysis shown in

Figure 25 as both these corrosion product bands were detected on both steel coupon samples.

Similarly, there is no XRD data for the steel coupon samples exposed in the aerobic environment

since no corrosion product was detected upon acetone washing the sludge layer off the coupons.

65

Figure 43. XRD of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel samples in an

anaerobic (3UC61 and 3UC63) environment.

Lepidocrocite and magnetite was detected as the corrosion products on steel coupon

3UC63 whereas magnetite was the only corrosion product detected on steel coupon 3UC61 as

depicted by Figure 43. Raman analysis from Figure 26 differs slightly from these XRD results.

Raman detected bands characteristic of lepidocrocite and magnetite on sample 3UC61, while

lepidocrocite was the only corrosion product found on steel coupon 3UC63.

66

Figure 44. XRD of 6 months 1018 steel coupons exposed in filtered ULSD fuel samples in an

anaerobic (3FC61 and 3FC63) environment.

Similar to steel coupon 3UC63 of Figure 43, Lepidocrocite and magnetite were the

corrosion products identified by XRD on steel coupon 3FC63 as depicted by Figure 44. On steel

coupon 3FC61, magnetite was the only corrosion product identified. Raman results from Figure

27 correlate well with steel coupon 3FC63, but in the case of steel coupon 3FC61, no corrosion

product bands could be detected. As explained before, the Raman could not detect any bands due

to the very little corrosion product on the steel coupon, but fortunately in the case of XRD

analysis, corrosion product could be detected in the form of magnetite.

67

Figure 45. XRD of 6 months 1018 steel coupons exposed in filtered and unfiltered ULSD fuel

samples in a selective aerobic (3FM63 and 3UM61) environment.

Lepidocrocite and goethite were the two corrosion products found on both steel samples

3FM63 and 3UM61 as depicted by Figure 45. These two corrosion products were also revealed

by Raman analysis of Figure 28.

68

Figure 46. XRD of 6 months 1018 steel coupons exposed in unfiltered ULSD fuel samples in an

aerobic (3UO61) environment.

Figure 46 depicts lepidocrocite and goethite as the corrosion products identified on the

top part of steel coupon 3UO61 whereas only lepidocrocite was identified as the only corrosion

product on the bottom of steel coupon 3UO61. Again, these results correlate well with Raman

results of Figure 29.

69

Figure 47. XRD of 6 months 1018 steel coupons exposed in filtered ULSD fuel samples in an

aerobic (3FO63) environment.

Lepidocrocite and hematite were detected as corrosion products on both the top and

bottom parts of steel coupon 3FO63 as depicted by Figure 47. Raman analysis of Figure 30

reveals lepidocrocite and a slightly different iron oxide, goethite, as the two corrosion products

for steel coupon 3FO63. Hematite was not detected by the Raman.

Similarly, the following figures depict the results obtained via XRD for the 1 year

exposure time period.

70

Figure 48. XRD of 1 year 1018 steel coupons exposed in unfiltered B100 fuel samples in an

anaerobic (1UC12), selective aerobic (1UM11), and aerobic (1UO12) environments.

Similar to the 6 month exposure of Figure 39, XRD results depicted by Figure 48,

revealed iron formate hydrate as the main corrosion product on 1018 steel coupons 1UM11 and

1UO12. As for steel coupon 1UC12, no corrosion product could be detected by XRD. Raman

analysis from Figures 30, 31, and 32 revealed bands characteristic of lepidocrocite and an

unknown band which could possibly be iron formate hydrate for steel coupons 1UC12 and

1UO12. Raman was unable to determine corrosion product on sample 1UM11.

71

Figure 49. XRD of 1 year 1018 steel coupons exposed in filtered B100 fuel samples in an

anaerobic (1FC13), selective aerobic (1FM12), and aerobic (1FO12) environments.

XRD analysis reveals iron formate hydrate for steel coupons 1FC13 and 1FO12 whereas

steel coupon 1FM12 showed hematite and lepidocrocite as corrosion products as depicted by

Figure 49. In contrast to the XRD results obtained, Raman results of Figures 30, 31, and 33

revealed lepidocrocite as the corrosion products for steel coupons 1FC13, 1FM12, and 1FO12. In

addition, maghemite was also found on steel coupon 1FO12.

72

Figure 50. XRD of 1 year 1018 steel coupons exposed in unfiltered B20 fuel samples in an

anaerobic (2UC12) and selective aerobic (2UM11) environment.

Iron formate hydrate was the corrosion product observed on steel coupon 2UM11 as

depicted by Figure 50. There was too little corrosion product for XRD analysis on steel coupon

2UC12. Raman analysis of Figure 34 revealed different results as both steel coupon samples

showed bands characteristic of lepidocrocite as the corrosion product. As for the case of the

previous analysis performed with Raman, there is no XRD data for the steel coupon samples

exposed in the aerobic environment since no corrosion product was detected upon acetone

washing the sludge layer off the coupons.

73

Figure 51. XRD of 1 year 1018 steel coupons exposed in filtered B20 fuel samples in an

anaerobic (2UC12) and selective aerobic (2UM11) environment.

Faint iron formate hydrate peaks were found on sample 2FM13 as depicted by Figure 51.

Again, there was too little corrosion product for XRD analysis on steel coupon 2FC13.

Characteristic bands of lepidocrocite was revealed in Raman analysis for both coupon samples as

depicted by Figure 35. Also on steel coupon 2FM13, an unknown band was detected which as

stated previously could possibly belong to iron formate hydrate. Similarly, there is no XRD data

for the steel coupon samples exposed in the aerobic environment since no corrosion product was

detected upon acetone washing the sludge layer off the coupons.

74

Figure 52. XRD of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel

samples in an anaerobic (3FC11, 3FC13, and 3UC11) environment.

XRD analysis revealed lepidocrocite and magnetite as the corrosion products found in all

steel coupon samples as depicted by Figure 52. Raman results of Figure 36 are also in agree with

XRD analysis as bands characteristic of lepidocrocite and magnetite were detected.

75

Figure 53. XRD of 1 year 1018 steel coupons exposed in filtered and unfiltered ULSD fuel

samples in a selective aerobic (3UM11 and 3FM13) environment.

XRD results reveal lepidocrocite and iron oxide hydroxide as the corrosion products for

both steel samples as depicted by Figure 53. Raman results of Figure 37 only detected

characteristic bands pertaining to lepidocrocite for both samples. The additional iron oxide

hydroxide was not detected by Raman.

76

Figure 54. XRD of 1 year 1018 steel coupon exposed in unfiltered ULSD fuel samples in an

aerobic (3UO11) environment.

XRD analysis revealed lepidocrocite as the corrosion product on the bottom portion of

steel coupon 3UO11 as depicted by Figure 54. Unfortunately, for the top portion of 3UO11,

XRD was unable to detect any reasonable corrosion product. The Raman results of Figure 38

also agree with XRD analysis and was able to detect a slight band characteristic of maghemite

for the top portion of steel coupon 3UO11.

77

Figure 55. XRD of 1 year 1018 steel coupon exposed in filtered ULSD fuel samples in an

aerobic (3FO12) environment.

Goethite and magnetite were the two corrosion products detected by XRD analysis in

both steel coupons as depicted by Figure 55. Raman results of Figure 38 also agree and

compliment these results.

78

5.5. SEM/EDXA

The SEM/EDXA analysis of this section is viewed more as supplementary to the Raman

and XRD analysis. The corrosion product form listed in the SEM/EDXA analysis serves only as

a hypothesis as to the types of products found, and are not definitive as in the case of the Raman

and XRD. This form column was added based on SEM/EDXA analysis involving the atomic

percentages of elements found. Therefore, corrosion products are listed based on these atomic

percentages but are in no way definitive or representative in the actual corrosion products on the

1018 steel coupons. Hence, SEM/EDXA analysis is here to compliment the corrosion product

findings of both Raman and XRD analyses.

Due to the vast amount of data obtained through SEM/EDXA analysis, only data of

importance is presented in this section. The remaining SEM/EDXA data can be found in the

appendix. The following figures depict the results obtained via SEM/EDXA for the 6 month


79

Figure 56. SEM analysis of 1018 steel coupon (1UC61) exposed in unfiltered B100 fuel-water

mixture exposed in an anaerobic environment.

For the SEM/EDXA analysis depicted by Figure 56, EDXA spectra reveals possible

corrosion product high in iron and oxygen, which is indicative of possible iron oxides and

Processing option : All elements analysed

Spectrum In stats. C O Mn Fe Form* Spectrum 1 Yes 38.69 33.78 27.53 Fe3O4 Spectrum 2 Yes 31.00 52.92 0.15 15.93 Fe(OH)3 Spectrum 3 Yes 41.58 58.42 Fe3O4 Spectrum 4 Yes 27.81 41.68 30.52 Fe3O4 Spectrum 5 Yes 34.09 50.69 15.22 Fe(OH)3 Spectrum 6 Yes 28.01 64.98 7.01 Spectrum 7 Yes 37.30 53.24 9.46 Spectrum 8 Yes 34.61 57.32 8.07 Spectrum 9 Yes 27.63 66.01 6.36 Max. 41.58 66.01 0.15 58.42 Min. 27.63 33.78 0.15 6.36

All results in atomic% *Based on the ratios of iron oxides and hydroxides.

80

hydroxides of the form Fe3O4 and Fe(OH)3. Carbon is also found which is indicative of fuel that

may have remained on the sample.

Figure 57. SEM analysis of 1018 steel coupon (2FC63) exposed in filtered B20 fuel-water



corrosion product high in iron and oxygen, which is indicative of possible iron oxide and


Spectrum In stats. C O Fe Form* Spectrum 1 Yes 30.94 56.12 12.93 Spectrum 2 Yes 43.32 49.79 6.89 Spectrum 3 Yes 35.01 47.05 17.94 Fe(OH)3 Spectrum 4 Yes 11.82 88.18 Spectrum 5 Yes 33.30 38.85 27.85 Fe3O4 Spectrum 6 Yes 26.91 54.60 18.50 Fe(OH)3 Max. 43.32 56.12 88.18 Min. 26.91 11.82 6.89


81

hydroxide in the form of Fe3O4 and Fe(OH)3. Carbon was again found which is indicative of fuel

that may have remained on the sample.

Figure 58. SEM analysis of 1018 steel coupon (3UO61) exposed in unfiltered ULSD fuel-water

mixture exposed in an aerobic environment.


corrosion product high in iron and oxygen, which is indicative of possible iron oxide-hydroxide


Spectrum In stats. C O Fe Form* Spectrum 1 Yes 37.81 33.42 28.77 Spectrum 2 Yes 34.43 52.10 13.47 Spectrum 3 Yes 37.76 43.85 18.39 Spectrum 4 Yes 39.03 49.86 11.11 Spectrum 5 Yes 35.14 42.96 21.90 FeO(OH) Spectrum 6 Yes 35.16 56.20 8.64 Max. 39.03 56.20 28.77 Min. 34.43 33.42 8.64


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of the form FeO(OH). The Carbon is again indicative of fuel that may have remained on the

sample.

Similarly, the following figures depict the results obtained via SEM/EDXA for the 1 year


Figure 59. SEM analysis of 1018 steel coupon (3UC11) exposed in unfiltered ULSD fuel-water



Spectrum In stats. C O Fe Form* Spectrum 1 Yes 54.09 27.33 18.58 Fe2O3 Spectrum 2 Yes 45.75 33.63 20.62 Fe2O3 Spectrum 3 Yes 75.06 15.73 9.22 Fe2O3 Spectrum 4 Yes 36.15 51.37 12.48 Spectrum 5 Yes 53.00 35.29 11.71 Fe(OH)3 Spectrum 6 Yes 49.56 36.05 14.39 Fe(OH)3 Spectrum 7 Yes 40.31 43.37 16.32 Fe(OH)3 Max. 75.06 51.37 20.62 Min. 36.15 15.73 9.22


83


corrosion product high in iron and oxygen, which is indicative of possible iron oxides and

hydroxides of the form Fe2O3 and Fe(OH)3. Carbon is also found which is indicative of fuel that

may have remained on the sample.

Figure 60. SEM analysis of 1018 steel coupon (1UO12) exposed in unfiltered B100 fuel-water



Spectrum In stats. C O Fe Form* Spectrum 1 Yes 39.61 55.79 4.59 Spectrum 2 Yes 28.18 63.82 7.99 Spectrum 3 Yes 37.83 55.10 7.07 Spectrum 4 Yes 100.00 Spectrum 5 Yes 35.58 55.53 8.89 Spectrum 6 Yes 36.33 47.20 16.47 Fe(OH)3 Max. 39.61 63.82 100.00 Min. 28.18 47.20 4.59


84


corrosion product high in iron and oxygen, which is indicative of possible iron hydroxide of the

form Fe(OH)3. Carbon is also found which is indicative of fuel that may have remained on the

sample.

Figure 61. SEM analysis of 1018 steel coupon (3FO12) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Fe Form* Spectrum 1 Yes 51.02 40.89 8.09 Spectrum 2 Yes 52.81 27.17 20.02 Fe3O4 Spectrum 3 Yes 41.00 26.42 32.58 Spectrum 4 Yes 14.29 4.34 81.37 Spectrum 5 Yes 56.99 34.73 8.28 Max. 56.99 40.89 81.37 Min. 14.29 4.34 8.09


85


corrosion product high in iron and oxygen, which is indicative of possible iron oxide of the form

Fe3O4. The Carbon is again indicative of fuel that may have remained on the sample.

86

Chapter 6

pH, TAN, DO and Mass Loss

6.1. pH The following tables depict the pH readings for the 6 month experimental exposures.

Table 9. pH results for 6 month steel coupon samples exposed in an anaerobic environment.

Fuel Type Fuel Water B100 5.26 4.39

B100F 5.19 4.46 B20 4.81 5.22

B20F 4.10 5.15 ULSD 3.66 5.77

ULSDF 3.98 5.76 Table 10. pH results for 6 month steel coupon samples exposed in an aerobic environment.


B100F 4.26 3.98 B20 3.74 4.11

B20F 3.98 4.20 ULSD 3.90 5.32

ULSDF 3.25 5.47 Table 11. pH results for 6 month steel coupon samples exposed in a selective aerobic environment.


B100F 3.99 3.91 B20 3.94 4.54

B20F 3.94 4.69 ULSD 3.34 5.26

ULSDF 3.39 5.24 Table 12. pH results for B100, B20, and ULSD as received straight from the pump.

Fuel Type Fuel B100 4.18 B20 4.65

ULSD 4.49

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The following trends were observed from the pH results. Filtered and unfiltered B20 and

ULSD fuel-water mixtures revealed lower pH values in the fuel layer with respect to the water

layer as depicted by Tables 9, 10, and 11. Filtered and unfiltered B100 fuel-water mixtures

revealed the exact opposite trend with lower pH values observed in the water layer with respect

to the fuel layer as depicted by Tables 9, 10, and 11. Initial pH values of Table 12 also reveal that

B100 fuel-water mixtures increased in alkalinity as time progressed whereas B20 and ULSD

fuel-water mixtures increased in acidity as time progressed. Differences in pH values between

filtered and unfiltered fuels were negligible. B20 and ULSD fuel-water mixtures appeared to

follow similar trends probably due to the fact that B20 fuel contains 80% ULSD in its

composition.

Similarly, the following tables depict the pH readings for the 1 year experimental

exposures.

Table 13. pH results for 1 year steel coupon samples exposed in an anaerobic environment.


B100F 3.70 4.09 B20 3.78 4.23

B20F 3.42 4.79 ULSD 4.01 4.80

ULSDF 3.58 4.53 Table 14. pH results for 1 year steel coupon samples exposed in an aerobic environment.


B100F 4.28 4.74 B20 3.45 4.22

B20F 3.90 4.36 ULSD 3.15 4.02

ULSDF 3.14 3.99

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Table 15. pH results for 1 year steel coupon samples exposed in a selective aerobic environment. Fuel Type Fuel Water

B100 3.95 4.27 B100F 3.41 3.75

B20 2.87 4.05 B20F 3.81 4.39 ULSD 3.23 4.01

ULSDF 3.18 4.41 Table 16. pH results for 1 year old B100, B20, and ULSD fuels.

Fuel Type Fuel B100 5.61 B20 4.24

ULSD 4.40 The 1 year pH results differed from the 6 month results as all fuel types revealed a

decrease in pH value in the fuel layer with respect to the water layer. The 1 year old pH results of

Table 16 also revealed that all fuels increased with acidity as time progressed.

89

6.2. TAN

The following table depicts the TAN readings for the 6 month experimental exposures.

The figures that accompany the table are a plot of respective pH values from Tables 9 to 11 with

corresponding TAN values.

Table 17. 6 month TAN results for fuels in an anaerobic, aerobic, and selective aerobic environment.

Fuel Type TAN (Anaerobic) TAN (Aerobic) TAN (Sel. Aerobic)B100 2.00 2.00 2.00

B100F 1.03 2.00 1.97 B20 0.00 2.00 1.00

B20F 0.00 2.00 0.80 ULSD 0.00 0.40 0.03

ULSDF 0.00 0.17 0.00

TAN vs. pH (Anaerobic)

0.000.501.001.502.002.50

3.00 3.50 4.00 4.50 5.00 5.50

pH

TAN

Figure 62. 6 month plot of TAN vs. pH of fuels in an anaerobic environment.

90

TAN vs. pH (Aerobic)

0.000.501.001.502.002.50

3.00 3.50 4.00 4.50 5.00 5.50

pH

TAN

Figure 63. 6 month plot of TAN vs. pH of fuels in an aerobic environment.

TAN vs. pH (Selective Aerobic)

0.000.501.001.502.002.50

3.00 3.50 4.00 4.50 5.00

pH

TAN

Figure 64. 6 month plot of TAN vs. pH of fuels in a selective aerobic environment.

These TAN vs. pH plots of Figures 62 to 64 reveal the trend that TAN increases as pH

values increase (become more alkaline). As mentioned earlier, TAN is essentially defined as the

number of milligrams of KOH required to neutralize the acidity in one gram of oil [19].

Therefore, oil with high TAN values, approximately > 0.5, are less desirable since they have

been known to cause problems with respect to corrosion and refinery processes [19].

Similarly, the following table depicts the TAN readings for the 1 year experimental

exposures. The figures that accompany the table are a plot of respective pH values from Tables

13 to 15 with corresponding TAN values.

91

Table 18. 1 year TAN results for fuels in an anaerobic, aerobic, and selective aerobic environment.

Fuel Type TAN (Anaerobic) TAN (Aerobic) TAN (Sel. Aerobic)B100 0.10 2.00 2.00

B100F 0.83 2.00 2.00 B20 0.00 2.00 2.00

B20F 0.00 2.00 2.00 ULSD 0.00 0.87 0.30

ULSDF 0.10 0.83 0.33

Figure 65. 1 year plot of TAN vs. pH of fuels in an anaerobic environment.

Figure 66. 1 year plot of TAN vs. pH of fuels in an aerobic environment.

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Figure 67. 1 year plot of TAN vs. pH of fuels in a selective aerobic environment.

Again, for the most part, these TAN vs. pH plots of Figures 65 to 67 reveal the trend that

TAN increases as pH values increase (become more alkaline). There are some slight deviations

with respect to the anaerobic and selective aerobic environment of Figures 65 and 67. In the

anaerobic setting of Figure 65, the TAN values virtually remain the same at a value of 0, whereas

in the selective aerobic setting of Figure 67, the exact opposite is seen where the majority TAN

values are seen at a maximum value of 2.

To fully understand the relationships between pH and TAN values, a graph of both values

were plotted. The following plots are for the 6 month time exposure period.

93

Figure 68. Plot of pH and TAN values for 6 month anaerobic environment.

Figure 69. Plot of pH and TAN values for 6 month aerobic environment.

94

Figure 70. Plot of pH and TAN values for 6 month selective aerobic environment.

Trends seen from Figures 68 to 70 reveal that as the pH of fuel increases (becomes more

alkaline) corresponding water pH values decrease (become more acidic) and corresponding TAN

values increase.

Similarly, the following plots are for the 1 year time exposure period.

Figure 71. Plot of pH and TAN values for 1 year anaerobic environment.

95

Figure 72. Plot of pH and TAN values for 1 year aerobic environment.

Figure 73. Plot of pH and TAN values for 1 year selective aerobic environment.

Trends from Figures 71 to 73 are more difficult to see in comparison to the 6 month

counterparts of Figures 68 to 70. For the case of aerobic and selective aerobic environments of

Figures 72 and 73, as fuel pH values increase (become more alkaline), corresponding TAN

values increase. Water pH values of the aerobic environment from Figure 72 also show an

increase in value (become more alkaline) as fuel pH values increase (become more alkaline).

Trends for the anaerobic environment of Figure 71 are hard to see.

96

It is important to note that the disparity between pH and TAN values seen in the data is

not atypical. pH is known to be an apparent representation on how corrosive the fuel may be, but

does not indicate the acidic or alkaline constituents [23]. TAN measures the acidic or alkaline

constituents but gives less of a representation on how corrosive the fuel may be [23]. In

comparison to pH, TAN has a better ability to detect weak acids, which do not readily dissociate

in water [23]. Thus, pH and TAN measure different aspects of the fuel’s acidic or alkaline

character.

6.3. DO

The following tables are the DO results obtained for B100, B20, and ULSD fuel-water

mixtures exposed in their respective environments (aerobic, selective aerobic, and anaerobic) for

an equilibrium duration period of 1 hour. DO measurements were taken in the water layer of the

fuel-water mixtures as depicted by Figure 5.

Table 19. DO results for B100 fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment.

Aerobic Selective Aerobic Anaerobic Time (min.)

DO (ppm)

Time (min.)

DO (ppm)

Time (min.)

DO (ppm)

0 7.14 0 6.67 0 6.54 5 6.90 5 6.67 5 6.55 10 6.73 10 6.67 10 6.55 15 6.57 15 6.68 15 6.54 20 6.60 20 6.67 20 6.52 25 6.61 25 6.66 25 6.49 30 6.63 30 6.65 30 6.45 35 6.65 35 6.64 35 6.41 40 6.66 40 6.62 40 6.39 45 6.67 45 6.61 45 6.37 50 6.68 50 6.60 50 6.37 55 6.69 55 6.58 55 6.37 60 6.69 60 6.57 60 6.36

97

Table 20. DO results for B20 fuel fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment.


DO (ppm)

Time (min.)

DO (ppm)

Time (min.)

DO (ppm)

0 6.84 0 6.98 0 7.06 5 6.84 5 6.99 5 7.06 10 6.84 10 6.99 10 7.07 15 6.81 15 6.99 15 7.10 20 6.78 20 7.00 20 7.11 25 6.79 25 7.02 25 7.11 30 6.83 30 7.02 30 7.12 35 6.86 35 7.02 35 7.13 40 6.90 40 7.02 40 7.15 45 6.93 45 7.04 45 7.15 50 6.96 50 7.05 50 7.16 55 6.97 55 7.06 55 7.18 60 6.98 60 7.06 60 7.19

Table 21. DO results for ULSD fuel fuel-water mixture in an aerobic, selective aerobic, and anaerobic environment.


DO (ppm)

Time (min.)

DO (ppm)

Time (min.)

DO (ppm)

0 8.31 0 7.93 0 7.66 5 8.26 5 7.91 5 7.67 10 8.25 10 7.89 10 7.67 15 8.23 15 7.86 15 7.69 20 8.23 20 7.81 20 7.70 25 8.21 25 7.78 25 7.69 30 8.15 30 7.74 30 7.68 35 8.09 35 7.72 35 7.67 40 8.06 40 7.70 40 7.68 45 8.04 45 7.68 45 7.72 50 8.01 50 7.68 50 7.76 55 7.98 55 7.68 55 7.78 60 7.96 60 7.66 60 7.78

The results for most of the fuel-water mixtures as depicted by Tables 19 to 21, the

aerobic environment setting had the highest concentration of DO with the anaerobic having the

lowest concentration of DO. Therefore, more importantly, these results indicate that even in

98

anaerobic environments, there is still DO present within the water layer of the fuel-water

mixture.

6.4. Mass Loss The following tables depict the mass loss results for the 6 month exposure period.

Table 22. Mass loss results for 1018 steel coupons exposed for 6 months in unfiltered fuels in an aerobic, selective aerobic, and anaerobic environment.

Sample Total Mass Loss Avg (g) STDEV (+/-) PR (mm/year)

B100 Anaerobic 0.3719 0.0167 0.1199

B100 Aerobic 0.1987 0.0115 0.0641

B100 Sel. Aerobic 0.2142 0.0382 0.0691

B20 Anaerobic 0.0347 0.0455 0.0112

B20 Aerobic 0.2074 0.0060 0.0669

B20 Sel. Aerobic 0.0735 0.1152 0.0237

ULSD Anaerobic 0.1654 0.1645 0.0533

ULSD Aerobic 0.2734 0.0182 0.0881

ULSD Sel. Aerobic 0.3256 0.0098 0.1050

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Table 23. Mass loss results for 1018 steel coupons exposed for 6 months in filtered fuels in an aerobic, selective aerobic, and anaerobic environment.


B100F Anaerobic 0.0715 0.0350 0.0231

B100F Aerobic 0.1474 0.0104 0.0475

B100F Sel. Aerobic 0.0642 0.0048 0.0207

B20F Anaerobic 0.0261 0.0175 0.0084

B20F Aerobic 0.1835 0.0027 0.0592

B20F Sel. Aerobic 0.1358 0.1155 0.0438

ULSDF Anaerobic 0.1123 0.1264 0.0362

ULSDF Aerobic 0.2241 0.0055 0.0723

ULSDF Sel. Aerobic 0.2659 0.0192 0.0857

These mass loss results reveal that filtered fuel-water mixtures suffer less corrosion

damage and have lower penetration rates when compared to their counterpart unfiltered fuel-

water mixtures as seen in Tables 22 and 23. In terms of environment condition, there are some

trends that can be seen. For example, in the case of 1018 steel coupons immersed in both filtered

and unfiltered B20 fuel-water mixtures, the aerobic environment showed the greatest mass loss

with anaerobic environment the least amount of mass loss. Similarly, for 1018 steel coupons

immersed in both filtered and unfiltered ULSD fuel-water mixtures, the selective aerobic

100

environment showed the greatest mass loss with anaerobic environment the least amount of mass

loss. For the B100 fuel-water mixtures, the highest corrosion rate was observed in the unfiltered

anaerobic samples. In general, the corrosion rates were higher in the unfiltered B100 fuel-water

mixtures compared to the filtered B100 fuel-water mixtures.

Similarly, the following tables depict the mass loss results for the 1 year exposure period.

Table 24. Mass loss results for 1018 steel coupons exposed for 1 year in unfiltered fuels in an aerobic, selective aerobic, and anaerobic environment.


B100 Anaerobic 0.0224 0.0110 0.0072

B100 Aerobic 0.2587 0.0065 0.0834

B100 Sel. Aerobic 0.3489 0.0108 0.1125

B20 Anaerobic 0.0107 0.0008 0.0034

B20 Aerobic 0.3543 0.0127 0.1142

B20 Sel. Aerobic 0.2323 0.0569 0.0749

ULSD Anaerobic 0.0285 0.0185 0.0092

ULSD Aerobic 0.4141 0.0279 0.1335

ULSD Sel. Aerobic 0.6083 0.0256 0.1961

101

Table 25. Mass loss results for 1018 steel coupons exposed for 1 year in filtered fuels in an aerobic, selective aerobic, and anaerobic environment.


B100F Anaerobic 0.2120 0.2993 0.0684

B100F Aerobic 0.2680 0.0215 0.0864

B100F Sel. Aerobic 0.2585 0.0383 0.0833

B20F Anaerobic 0.0090 0.0007 0.0029

B20F Aerobic 0.3200 0.0203 0.1032

B20F Sel. Aerobic 0.2129 0.0726 0.0687

ULSDF Anaerobic 0.4088 0.1847 0.1318

ULSDF Aerobic 0.3608 0.0260 0.1163

ULSDF Sel. Aerobic 0.5086 0.0132 0.1640

Again, similar trends can be seen with the 1 year exposure mass loss results of Tables 24

and 25. Most of the results reveal again that filtered fuel-water mixtures suffer less corrosion

damage and less penetration rates in comparison to their unfiltered fuel-water mixture

counterparts. In terms of specific environmental trends, the 1 year mass loss data almost matches

trends seen in the 6 month mass loss data. For 1018 steel coupons exposed in filtered and

unfiltered ULSD fuel-water mixtures, the selective aerobic environment showed the highest mass

loss with the anaerobic environment the least for unfiltered ULSD fuel-water mixture and

102

aerobic least for filtered ULSD fuel-water mixture. Again, for 1018 steel coupons exposed in

filtered and unfiltered B20 fuel-water mixtures, the aerobic environment showed the highest

mass loss with the anaerobic environment the least. For the B100 fuel-water mixtures, no

significant difference in trends was observed comparing the filtered and unfiltered fuel-water

mixtures, however, the corrosion rate in both fuel-water mixtures were higher in the aerobic and

selective aerobic conditions.

103

Chapter 7

Microbial Contamination

No microbial contamination was found solely in the fuel layer of the fuel-water mixtures

of the experiment. Microbial contamination was only found to an extent within the water and

interface regions of the fuel-water mixtures. For the case of the 6 month exposure part of the

experiment, a fungi was successfully isolated and identified. This particular fungi was found

only within the water/interface regions of the 1018 steel coupons exposed in unfiltered B20 fuel-

water mixtures set in a anaerobic environment (2UC63) and selective aerobic environment

(2UM62).

Figure 74. Fungi culture, 18S rRNA sequencing yields a 99% match to the fungi Paecilomyces

saturatus.

104

Figure 74 depicts the isolated fungus cultured on specialized fungi media sab dex agar.

With the help of Dr. Stuart Donachie’s lab from the department of microbiology at University of

Hawaii at Manoa, and his graduate student, Mark Chaplin, successful identification of this fungi

was possible through 18S rRNA sequencing. The following depicts the sequences obtained for

the forward primers (18sF) and reverse primers (18sR) of the fungi:

18sF: TGCATGTCTAAGTATAAGCAATCTATACGGTGAAACTGCGAATGGCTCATTAAATCAGTTATCGTTTATTTGATAGTACCTTGCTACATGGATACCTGTGGTAATTCTAGAGCTAATACATGCTGAAAACCTCGACTTCGGAAGGGGTGTATTTATTAGATAAAAAACCAATGCCCTTCGGGGCTCCTTGGTGATTCATAATAACTTAACGAATCGCATGGCCTTGCGCCGGCGATGGTTCATTCAAATTTCTGCCCTATCAACTTTCGATGGTAGGATAGTGGCCTACCATGGTGGCAACGGGTAACGGGGAATTAGGGTTCGATTCCGGAGAGGGAGCCTGAGAAACGGCTACCACATCCAAGGAAGGCAGCAGGCGCGCAAATTACCCAATCCCGACACGGGGAGGTAGTGACAATAAATACTGATACAGGGCTCTTTTGGGTCTTGTAATCGGAATGAGTACAATCTAAATCCCTTAACGAGGAACAATTGGAGGGCAAGTCTGGTGCCAGCAGCCGCGGTAATTCCAGCTCCAATAGCGTATATTAAAGTTGTTGCAGTTAAAAAGCTCGTAGTTGAACCTTGGGTCTGGCTGGCCGGTCCGCCTCACCGCGAGTACTGGTCCGGCTGGACCTTTCCTTCTGGGGAACCCCATGGCCTTCACTGGCCGTGGCGGGGAACCAGGACTTTTACTGTGAAAAAATTAGAGTGTTCAAAGCAGGCCTTTGCTCGAATACATTAGCATGGAATAATAGAATAGG 18sR: ACTTCCTCTAAATGACCAAGTTTGACCAACTTTCCGGCTCTGGGCGGTCGTTGCCAACCCCCCTGAGCCAGTCCGAAGGCCTCACTGAGCCATTCAATCGGTAGTAGCGACGGGCGGTGTGTACAAAGGGCAGGGACGTAATCGGCACGAGCTGATGACTCGTGCCTACTAGGCATTCCTCGTTGAAGAGCAATAATTGCAATGCTCTATCCCCAGCACGACAGGGTTTAACAAGATTACCCAGACCTCTCGGCCAAGGTGATGTACTCGCTGGCCCTGTCAGTGTAGCGCGCGTGCGGCCCAGAACATCTAAGGGCATCACAGACCTGTTATTGCCGCGCACTTCCATCGGCTTGAGCCGATAGTCCCCCTAAGAAGCCAGCGGCCCGCAAACGCGGACCGGGCTATTTAAGGGCCGAGGTCTCGTTCGTTATCGCAATTAAGCAGACAAATCACTCCACCAACTAAGAACGGCCATGCACCACCATCCAAAAGATCAAGAAAGAGCTCTCAATCTGTCAATCCTTATTTTGTCTGGACCTGGTGAGTTTCCCCGTGTTGAGTCAAATTAAGCCGCAGGCTCCACGCCTTGTGGTGCCCTTCCGTCAATTTCTTTAAGTTTCAGCCTTGCGACCATACTCCCCCCAGAACCCAAAAACTTTGATTTCTCGTAAGGTGCCGAACGGGTCATCATAGAACACCGTCCGATCCCTAGTCGGCATAGTTTATGGTTAAGACTACGACGGTATCTGATCGTCTTCGATCCCCTAACTTTCGTTCCCTGATTAATGAAAACATCCTTGGCGAATGCTTTCGCAGTAGTTAGTCNTCAGCAAATCCAAGAATTTCACCTCTGACAGCTGAATACTGACGCCCCCGACTATCCCTA

105

Thus, with these sequences, a BLAST database search was performed to identify the specific

species of fungi cultured. The BLAST results obtained revealed a 99% match identity to the

fungi Paecilomyces saturatus.

According to literature, Paecilomyces variotti, which closely resembles Paecilomyces

saturatus, is the most commonly occuring species within this genus and is often found in foods,

soil, indoor air, and wood [24]. Paecilomyces strains are also often heat resistant and may

produce mycotoxins in contaminated pasteurised foods [25].

For the case of the 1 year exposure experiment, the same fungi was isolated and cultured

from the water/interface regions of the 1018 steel coupons exposed in unfiltered B20 fuel-water

mixtures set in an anaerobic environment (2UC13). However this time, no fungi was found in the

B20 fuel-water mixtures set in a selective aerobic environment as was the case in the 6 month

exposure. There was an additional bacteria isolate from the 1 year exposure. This bacteria was

successfully isolated and identified from the water/interface regions of the 1018 steel coupons

exposed in unfiltered ULSD fuel-water mixtures set in an anaerobic environment.

106

Figure 75. Bacteria isolate, 16S rRNA sequencing yields a 97% match to the bacteria Ralstonia

solanacearum.

Figure 75 depicts the isolated bacteria cultured on blood agar media. Following the

colony PCR procedure [21], successful identification of the bacteria was possible through the

use of 16S rRNA sequencing. To verify the size of the PCR products being amplified, a gel

electrophoresis was performed.

107

Figure 76. Gel electrophoresis of colony PCR products from bacteria isolate.

The gel electrophoresis depicted by Figure 76 clearly shows that the PCR products

amplified fall within the range of approximately 800 base pairs. This is determined by the first

column marked L which designates the DNA ladder in units of base pair. Columns 1 through 6

are the individual bacterial samples with column 3 and 6 as negative controls, hence no product

was seen in those columns. Columns 1 and 2 utilized forward and reverse primers of

concentration 0.5 µM whereas column 4 and 5 utilized forward and reverse primer

concentrations of 1 µM. Thus, primer concentration did not make any difference in the success

of the colony PCR performed.

108

The following depicts the sequences obtained for the forward primers (519F) and reverse

primers (1406R) of the bacteria:

519F: TTACTTACAGACGCTGGGCGTAAGCGTGCGCAGGCGGTTGTGCAAGACCGATGTGAAATCCCCGGGCTTAACCTGGGAATTGCATTGGTGACTGCACGGCTAGAGTGTGTCAGAGGGGGGTAGAATTCCACGTGTAGCATTGAAATGCGTACAGATGTGGAGGTCCCCCATGTTCCCTTCAT 1406R: GCCAATCAACGAGCATGCGTGATCCGCGATTACTAGCGATTCCAGCTTCACGTAGTCGAGTTGCAGACTACGATCCGGACTACGATGCATTTTCTGGGATTAGCTCCACCTCGCGGCTTGGCAACCCTCTGTATGCACCATTGTATGACGTGTGAAGCCCTACCCATAAGGGCCATGAGGACTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGCAGTCTCTCTAGAGTGCCCTTTCGTAGCAACTAGAGACAAGGGTTGCGCTCGTTGCGGGACTTAACCCAACATCTCACGACACGAGCTGACGACAGCCATGCAGCACCTGTGTCCACTTTCTCTTTCGAGCACCTAATGCATCTCTGCTTCGTTAGTGGCATGTCAAGGGTAGGTAAGGTT TT Thus, with these sequences, a BLAST database search was performed again to identify the

specific species of bacteria isolated. The BLAST results obtained revealed a 97% match identity

to the bacteria Ralstonia solanacearum.

According to literature, Ralstonia solanacearum is a soilborne gram-negative bacterium

that causes bacterial wilt in many crops [26]. This particular strain of bacteria has also been

found to be well adjusted to hydrocarbons, as a study performed in 2010 reveals that this bacteria

among others dominate the microorganism popluation within hydrocarbon contaminated soils

with respect to soils with no hydrocarbon contamination [27]. Hence it’s presence within the

1018 steel coupons exposed in unfiltered ULSD fuel-water mixtures set in an anaerobic

environment is no surprise.

109

The fungi and bacteria were the only two types of microorganisms that were isolated

from both 6 year exposures and 1 year exposures. Little is known whether or not they play a role

in corrosion.

110

Chapter 8

Summary

No microorganisms were detected in any part of the fuel layer of the fuel-water mixtures

used in these experiments. This agrees well with literature as microorganisms are only capable of

growth when fuels have been contaminated with water [5]. Microbial contamination was only

observed in a few fuel samples such as the ULSD fuel-water mixtures and B20 fuel-water

mixtures. As mentioned earlier, all microbial contamination was found within the fuel-water

layer interface or within the water layer itself. Although no direct evidence of bacteria was found

in the B100 fuels, the formation of sediments in the fuel within approximately 1 week of

dispensing fuel from the pump indicated microbial activity. In addition, filtered B100 fuel did

not form sediments and remained lucid for over one year.

Contrary to the preliminary 1 month exposure experiment which revealed many different

types of microbial contamination, the 6 month and 1 year exposure experiments were only able

to identify a single fungi and bacteria species. The length of duration for the time the samples

were exposed most likely decreased the amount of “culturable” microorganisms [28]. The

preliminary 1 month experiment exposed a B100 fuel-water mixture for 1 month; whereas, the

main experiment exposed fuel-water mixtures for 6 months and 1 year. According to literature,

bacteria seldom experience environmental conditions that allow prolonged continuous growth

[29]. On contrary, due to their fast exponential growth cycles, bacteria often consume required

nutrients efficiently and because of this, are nutritionally starved most of the time [29]. Bacteria

that are nutritionally starved then enter a stationary phase in which metabolic activities begin to

slow down until nutrients are again available [29]. Some bacteria however are unable to survive

111

such extended periods of starvation and die off [29]. In most cases, bacteria are known to enter a

viable but nonculturable (VBNC) state [28]. Bacteria in this state fail to grow on routine

bacteriological media on which they would normally grow and develop into colonies, but are

alive and capable of renewed metabolic activity [28]. Thus, in the case of the 6 month and 1 year

experiments, a hypothesis can be made that the majority of microorganisms died off and/or

entered into the VBNC state; whereas, the preliminary 1 month exposure experiment had

adequate nutritional levels enough to sustain bacterial growth.

Microorganisms isolated from the 1 month exposure experiment revealed 4 different

types of bacterial species isolated from the B100 fuel-water mixture. The specific bacterial

species (Figures 7 through 10) are typical of the types of microorganisms found within fuels [30].

The two microorganisms isolated from the 6 month and 1 year exposures (depicted by Figures 74

and 75) are also typical of common microorganisms found within fuels [30, 31].

Although few microorganisms were successfully cultured in the lab, their effects on

corrosion of 1018 steel can still be noted. Strong evidence for this can be found on the 1018 steel

coupons exposed to the B100-water mixture for the 6 month period. The corrosion rate in

unfiltered B100-water mixture in the anaerobic environment was more than 5 times higher than

in the anaerobic filtered B100-water mixture. The corrosion rate in the anaerobic unfiltered

B100-water mixture was also almost 2 times higher than the aerobic unfiltered B100-water

mixture. In the case of the filtered B100-water mixtures, corrosion rates were higher in the

aerated environments. Interestingly, for the 1 year exposure period, the unfiltered and filtered

B100-water mixtures shared similar trends in the corrosion behavior, where the corrosion rates in

the anaerobic environment was significantly lower than the aerated environments. This was

likely caused by dead or dormant bacteria in the unfiltered B100 fuel. The 1 year exposure

112

experiments were started approximately 1 month after the 6 month exposure experiments using

the same B100 fuel from the same lot. It is plausible that the population of active bacteria

dwindled during this 1 month period. Other evidence of microbial activity was observed in both

filtered and unfiltered B20 fuel-water mixtures exposed in aerobic conditions. As shown

previously in Figure 21, these steel coupons taken from the 6 month and 1 year exposure times

all revealed a thick sludge layer characteristic of microbial contamination in the form of

biofouling [5, 14, 18]. Figure 77 below depicts a before and after image of the steel coupon upon

acetone washing. Clearly, little to very little corrosion products remain upon acetone washing

which indicates that the corrosion products was embedded within the sludge layer.

Figure 77. Before and after acetone wash image of 1018 steel coupon exposed in B20 fuel-water


Although numerous attempts of culturing microorganisms from the sludge failed, the

sludge formation is indicative of microbiological activity. Mass loss data also supports this

hypothesis as steel coupons exposed in the aerobic environment observed mass loss greater than

7 times that of the respective selective aerobic environments as depicted in Tables 22 to 25.

113

Corrosion product analysis via Raman, XRD, and SEM/EDXA were successful in

characterizing the different forms of rust observed on 1018 steel coupons. Although the severity

of corrosion damage to coupons cannot be directly correlated to the presence of microorganisms,

the majority of the coupons experienced corrosion that occurred within the fuel-water interface

and water layers where microorganisms if any are able to survive. It was observed that for most

steel coupons, the fuel layer of the fuel-water mixtures served as a protective layer from

corrosion and MIC. Trends on the type of dominant corrosion product found on 1018 steel

coupons exposed to different fuel-water mixtures and environments were also revealed from

these experiments. The corrosion products lepidocrocite and iron formate hydrate are the

dominant corrosion products observed on 1018 steel coupons exposed in filtered/unfiltered B100

fuel-water mixtures exposed in all environmental conditions (Table 26). Table 26 also reveals

corrosion products lepidocrocite and magnetite as the dominant corrosion products observed on

1018 steel coupons exposed in filtered/unfiltered B20 fuel-water mixtures in all environmental

conditions; whereas, 1018 steel coupons exposed in ULSD fuel-water mixtures exposed in all

environmental conditions revealed dominant corrosion products lepidocrocite, magnetite, and

goethite.

114

Table 26. Summary of corrosion product found on 1018 steel coupons via Raman and XRD exposed in all environmental conditions for 6 months and 1 year.

Anaerobic Fuel Raman XRD B100 Lepidocrocite Iron Formate Hydrate

B100 Filtered Lepidocrocite Lepidocrocite, Iron Formate Hydrate B20 Lepidocrocite, Magnetite Lepidocrocite, Magnetite, Iron Formate Hydrate

B20 Filtered Lepidocrocite, Magnetite Lepidocrocite, Magnetite ULSD Lepidocrocite, Magnetite Lepidocrocite, Magnetite

ULSD Filtered Lepidocrocite, Magnetite Lepidocrocite, Magnetite

Aerobic Fuel Raman XRD B100 Lepidocrocite Iron Formate Hydrate

B100 Filtered Lepidocrocite Iron Formate Hydrate B20 N/A N/A

B20 Filtered N/A N/A ULSD Lepidocrocite, Goethite, Maghemite Lepidocrocite, Goethite

ULSD Filtered Lepidocrocite, Goethite Hematite, Goethite, Magnetite

Selective Aerobic Fuel Raman XRD B100 Lepidocrocite Iron Formate Hydrate

B100 Filtered Lepidocrocite Lepidocrocite, Hematite B20 Lepidocrocite Iron Formate Hydrate

B20 Filtered Lepidocrocite, Magnetite Lepidocrocite, Magnetite, Iron Formate Hydrate ULSD Lepidocrocite, Goethite Lepidocrocite, Goethite, Iron Oxide Hydroxide

ULSD Filtered Lepidocrocite, Goethite Lepidocrocite, Goethite, Iron Oxide Hydroxide

The results obtained from the pH and TAN experiments revealed that pH values of the

fuel and water layers are more indicative of the severity of corrosion for the 1018 steel coupons

exposed in the ULSD fuel-water mixtures as depicted below by Figures 84 and 85; whereas,

TAN values are more indicative of the severity of corrosion for the 1018 steel coupons exposed

in B100 fuel-water mixtures (Figure 80). This disparity is clearly shown by pH value results of

Tables 9, 10, 11, 13, 14, and 15, and TAN value results of Tables 17 and 18, where the pH of

ULSD fuels are very acidic, with values < 4 in contrast to respectively very low TAN values

115

ranging from 0 to < 1. This indicates the fuels are not acidic. Hence, the pH and TAN values are

inconsistent. When compared to the mass loss data tabulated in Tables 22 through 25, 1018 steel

coupons exposed in the ULSD fuel-water mixtures are reported to have high mass loss values

and high penetration rates that directly correspond with low pH values. Hence, TAN values do

not correlate as well as pH values with respect to 1018 steel coupons exposed in ULSD fuel-

water mixtures as depicted below by Figure 86. The exact opposite trend is seen in the case of

1018 steel coupons exposed in B100 fuel-water mixtures. For the case of 1018 steel coupons

exposed in the B100 fuel-water mixtures, pH values from Tables 9, 10, 11, 13, 14, and 15 reveal

less acidic values, often > 4, but TAN values from Tables 17 and 18 reveal high values often

reaching the maximum value of 2. This indicates the fuels are very acidic. Hence, the pH and

TAN values are inconsistent. Again, when compared to the mass loss data tabulated in Tables 22

through 25, 1018 steel coupons exposed in the B100 fuel-water mixtures are reported to have

high mass loss values and high penetration rates that directly correspond with high TAN values.

Therefore, in this case, pH values do not correlate as well as TAN values with respect to 1018

steel coupons exposed in B100 fuel-water mixtures as depicted below by Figures 78 and 79. Due

to the fact that B20 fuel contains 80% ULSD fuel, corrosion of 1018 steel coupons exposed in

B20 fuel-water mixtures appear to correlate with both pH and TAN values as depicted below by

Figures 81 through 83. Again, as explained earlier, it is important to note that the disparity

between pH and TAN values seen in the data is not atypical. pH is known to be an apparent

representation on how corrosive the fuel may be, but does not indicate the acidic or alkaline

constituents [23]. TAN measures the acidic or alkaline constituents but gives less of a

representation on how corrosive the fuel may be [23]. In comparison to pH, TAN has a better

116

ability to detect weak acids, which do not readily dissociate in water [23]. Thus, pH and TAN

measure different aspects of the fuel’s acidic or alkaline character.

Figure 78. Penetration rate vs. pH (fuel layer) of 1018 steel exposed in all environmental

conditions for 6 months/1 year in filtered/unfiltered B100 fuel-water mixtures.

Figure 79. Penetration rate vs. pH (water layer) of 1018 steel exposed in all environmental


Figure 80. Penetration rate vs. TAN of 1018 steel exposed in all environmental conditions for 6

months/1 year in filtered/unfiltered B100 fuel-water mixtures.

117






months/1 year in filtered/unfiltered B20 fuel-water mixtures.

118


conditions for 6 months/1 year in filtered/unfiltered ULSD fuel-water mixtures.


conditions for 6 months/1 year in filtered/unfiltered ULSD fuel-water mixtures.


months/1 year in filtered/unfiltered ULSD fuel-water mixtures.

Due to the fact that only two microorganism were isolated from the 6 month and 1 year

exposures, correlations between MIC within biodiesels and ULSD are difficult to make. Hence,

future work involves incubating sterile fuel-water mixtures with the two microorganisms isolated

119

to determine their MIC on 1018 plain carbon steel. An additional, short-term corrosion test (e.g.,

one month exposure) should be performed on fresh diesel, and progressively older stored diesel

to study the possibility of microbial die-off on corrosion rates.

120

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123

Appendix The following figures depict the complete SEM/EDXA analysis of the 1018 steel

coupons for both 6 month and 1 year exposures.

124

Figure A1. SEM analysis of 1018 steel coupon (1UC61) exposed in unfiltered B100 fuel-water



Spectrum In stats. C O Mn Fe Spectrum 1 Yes 38.69 33.78 27.53 Spectrum 2 Yes 31.00 52.92 0.15 15.93 Spectrum 3 Yes 41.58 58.42 Spectrum 4 Yes 27.81 41.68 30.52 Spectrum 5 Yes 34.09 50.69 15.22 Spectrum 6 Yes 28.01 64.98 7.01 Spectrum 7 Yes 37.30 53.24 9.46 Spectrum 8 Yes 34.61 57.32 8.07 Spectrum 9 Yes 27.63 66.01 6.36 Max. 41.58 66.01 0.15 58.42 Min. 27.63 33.78 0.15 6.36

All results in atomic%

125

Figure A2. SEM analysis of 1018 steel coupon (1UO61) exposed in unfiltered B100 fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 40.08 51.88 8.04 Spectrum 2 Yes 59.87 27.98 12.15 Spectrum 3 Yes 43.74 35.30 20.97 Spectrum 4 Yes 35.18 33.60 31.22 Spectrum 5 Yes 46.32 45.32 8.36 Spectrum 6 Yes 46.59 47.33 6.08 Spectrum 7 Yes 50.66 41.11 8.23 Spectrum 8 Yes 100.00 Spectrum 9 Yes 43.72 50.81 5.47 Max. 59.87 51.88 100.00 Min. 35.18 27.98 5.47


126

Figure A3. SEM analysis of 1018 steel coupon (1UM63) exposed in unfiltered B100 fuel-water

mixture exposed in a selective aerobic environment.


Spectrum In stats. C O Mn Fe Spectrum 1 Yes 30.52 59.77 9.71 Spectrum 2 Yes 24.00 16.60 59.40 Spectrum 3 Yes 42.40 54.35 0.09 3.16 Spectrum 4 Yes 39.47 54.58 0.13 5.82 Spectrum 5 Yes 39.51 23.92 36.57 Spectrum 6 Yes 30.28 56.00 13.73 Max. 42.40 59.77 0.13 59.40 Min. 24.00 16.60 0.09 3.16


127

Figure A4. SEM analysis of 1018 steel coupon (1FC63) exposed in filtered B100 fuel-water



Spectrum In stats. C O Al Mn Fe Spectrum 1 Yes 28.43 0.68 70.88 Spectrum 2 Yes 21.47 60.43 18.10 Spectrum 3 Yes 23.48 76.52 Spectrum 4 Yes 16.75 51.09 32.16 Spectrum 5 Yes 34.16 42.29 23.55 Spectrum 6 Yes 17.60 19.49 1.58 61.33 Spectrum 7 Yes 100.00 Spectrum 8 Yes 34.66 65.34 Max. 34.66 60.43 1.58 0.68 100.00 Min. 16.75 19.49 1.58 0.68 18.10


128

Figure A5. SEM analysis of 1018 steel coupon (1FO62) exposed in filtered B100 fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 54.11 28.46 17.44 Spectrum 2 Yes 70.56 21.64 7.80 Spectrum 3 Yes 42.92 32.37 24.71 Spectrum 4 Yes 46.62 41.77 11.61 Spectrum 5 Yes 47.21 45.08 7.71 Spectrum 6 Yes 64.52 29.21 6.28 Spectrum 7 Yes 62.11 21.65 16.24 Mean 55.43 31.45 13.11 Std. deviation 10.49 9.12 6.70 Max. 70.56 45.08 24.71 Min. 42.92 21.64 6.28


129

Figure A6. SEM analysis of 1018 steel coupon (1FM63) exposed in filtered B100 fuel-water



Spectrum In stats. C O Na Fe Spectrum 1 Yes 72.04 12.02 15.94 Spectrum 2 Yes 73.69 21.90 4.41 Spectrum 3 Yes 66.69 25.42 7.88 Spectrum 4 Yes 68.02 28.86 3.12 Spectrum 5 Yes 66.96 31.18 0.16 1.70 Spectrum 6 Yes 71.23 20.20 8.57 Max. 73.69 31.18 0.16 15.94 Min. 66.69 12.02 0.16 1.70


130




Spectrum In stats. C O Mn Fe Spectrum 1 Yes 62.53 21.78 15.69 Spectrum 2 Yes 45.40 39.68 14.91 Spectrum 3 Yes 40.27 4.05 55.69 Spectrum 4 Yes 32.56 55.35 12.09 Spectrum 5 Yes 57.17 32.49 10.34 Spectrum 6 Yes 39.91 45.87 14.22 Spectrum 7 Yes 46.82 35.85 17.33 Spectrum 8 Yes 42.36 48.86 8.78 Max. 62.53 55.35 4.05 55.69 Min. 32.56 21.78 4.05 8.78


131




Spectrum In stats. C O Cr Mn Fe Spectrum 1 Yes 57.06 28.39 0.35 0.20 14.01 Spectrum 2 Yes 52.33 0.60 47.07 Spectrum 3 Yes 19.57 64.90 0.35 15.18 Spectrum 4 Yes 20.34 50.10 29.56 Spectrum 5 Yes 41.92 11.10 46.98 Spectrum 6 Yes 57.02 22.50 20.48 Max. 57.06 64.90 0.35 0.60 47.07 Min. 19.57 11.10 0.35 0.20 14.01


132


Spectrum In stats. C O Mn Fe Spectrum 1 Yes 18.93 2.86 78.21 Spectrum 2 Yes 26.29 56.38 0.17 17.17 Spectrum 3 Yes 58.24 36.34 0.10 5.32 Spectrum 4 Yes 40.71 12.44 46.84 Spectrum 5 Yes 28.99 3.02 67.98 Spectrum 6 Yes 100.00 Spectrum 7 Yes 3.98 96.02 Spectrum 8 Yes 62.38 21.47 16.15 Spectrum 9 Yes 52.05 17.39 30.55 Spectrum 10 Yes 24.21 4.73 71.06 Spectrum 11 Yes 100.00 Spectrum 12 Yes 100.00 Spectrum 13 Yes 100.00 Max. 62.38 56.38 0.17 100.00 Min. 18.93 2.86 0.10 5.32


Figure A9. SEM analysis of 1018 steel coupon (2FC63) exposed in filtered B20 fuel-water mixture exposed in an anaerobic environment.

133




Spectrum In stats. C O Fe Spectrum 1 Yes 45.80 30.92 23.28 Spectrum 2 Yes 26.48 6.64 66.88 Spectrum 3 Yes 59.32 6.00 34.68 Spectrum 4 Yes 73.05 18.43 8.52 Spectrum 5 Yes 37.26 62.74 Spectrum 6 Yes 23.39 2.51 74.10 Spectrum 7 Yes 50.98 12.49 36.54 Spectrum 8 Yes 53.42 36.75 9.83 Spectrum 9 Yes 71.53 18.14 10.33 Spectrum 10 Yes 70.03 22.28 7.69 Max. 73.05 36.75 74.10 Min. 23.39 2.51 7.69


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Figure A11. SEM analysis of 1018 steel coupon (3UC61) exposed in unfiltered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 70.51 15.19 14.30 Spectrum 2 Yes 61.54 29.02 9.44 Spectrum 3 Yes 57.51 23.62 18.88 Spectrum 4 Yes 83.51 11.98 4.51 Spectrum 5 Yes 54.56 34.58 10.86 Spectrum 6 Yes 61.07 26.16 12.77 Spectrum 7 Yes 57.30 30.79 11.91 Spectrum 8 Yes 44.00 27.07 28.93 Mean 61.25 24.80 13.95 Std. deviation 11.67 7.70 7.30 Max. 83.51 34.58 28.93 Min. 44.00 11.98 4.51


135

Figure A12. SEM analysis of 1018 steel coupon (3UO61) exposed in unfiltered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 37.81 33.42 28.77 Spectrum 2 Yes 34.43 52.10 13.47 Spectrum 3 Yes 37.76 43.85 18.39 Spectrum 4 Yes 39.03 49.86 11.11 Spectrum 5 Yes 35.14 42.96 21.90 Spectrum 6 Yes 35.16 56.20 8.64 Mean 36.56 46.40 17.05 Std. deviation 1.88 8.09 7.50 Max. 39.03 56.20 28.77 Min. 34.43 33.42 8.64


136

Figure A13. SEM analysis of 1018 steel coupon (3UM61) exposed in unfiltered ULSD fuel-

water mixture exposed in a selective aerobic environment.


Spectrum In stats. C O Fe Spectrum 1 Yes 26.74 60.11 13.15 Spectrum 2 Yes 2.90 97.10 Spectrum 3 Yes 23.66 61.48 14.86 Spectrum 4 Yes 20.20 61.49 18.31 Spectrum 5 Yes 17.17 62.55 20.29 Spectrum 6 Yes 32.17 51.52 16.31 Spectrum 7 Yes 25.62 60.95 13.43 Max. 32.17 62.55 97.10 Min. 17.17 2.90 13.15


137

Figure A14. SEM analysis of 1018 steel coupon (3FC61) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Mn Fe Spectrum 1 Yes 43.11 56.89 Spectrum 2 Yes 33.36 38.68 27.97 Spectrum 3 Yes 66.92 17.49 15.59 Spectrum 4 Yes 53.30 38.36 8.34 Spectrum 5 Yes 38.81 13.10 1.57 46.53 Spectrum 6 Yes 64.17 28.92 0.16 6.75 Spectrum 7 Yes 53.85 28.78 17.37 Spectrum 8 Yes 60.84 39.16 Spectrum 9 Yes 40.26 48.52 11.22 Spectrum 10 Yes 59.69 25.05 0.74 14.52 Max. 66.92 48.52 1.57 56.89 Min. 33.36 13.10 0.16 6.75


138

Figure A15. SEM analysis of 1018 steel coupon (3FO63) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Na Mg S Cl Ca Fe Spectrum 1 Yes 81.08 18.72 0.10 0.11 Spectrum 2 Yes 85.19 9.80 0.45 4.56 Spectrum 3 Yes 86.06 13.61 0.14 0.19 Spectrum 4 Yes 83.23 16.10 0.05 0.62 Spectrum 5 Yes 72.15 24.84 1.56 0.36 0.16 0.59 0.04 0.30 Spectrum 6 Yes 79.68 20.12 0.11 0.03 0.06 Spectrum 7 Yes 77.10 22.77 0.09 0.05 Max. 86.06 24.84 1.56 0.36 0.16 0.59 0.04 4.56 Min. 72.15 9.80 0.09 0.36 0.16 0.03 0.04 0.05


139

Figure A16. SEM analysis of 1018 steel coupon (3FM63) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Fe Tb Spectrum 1 Yes 100.00 Spectrum 2 Yes 20.81 61.49 17.69 Spectrum 3 Yes 20.55 52.59 26.86 Spectrum 4 Yes 25.64 58.88 15.48 Spectrum 5 Yes 18.41 59.86 21.73 Spectrum 6 Yes 7.80 1.17 89.74 1.29 Spectrum 7 Yes 12.98 44.00 43.02 Spectrum 8 Yes 5.33 2.63 92.03 Max. 25.64 61.49 100.00 1.29 Min. 5.33 1.17 15.48 1.29


140




Spectrum In stats. C O S Fe Spectrum 1 Yes 78.43 20.82 0.49 0.26 Spectrum 2 Yes 40.06 59.94 Spectrum 3 Yes 35.70 52.68 11.62 Spectrum 4 Yes 32.98 39.16 27.86 Max. 78.43 52.68 0.49 59.94 Min. 32.98 20.82 0.49 0.26


141

Figure A18. SEM analysis of 1018 steel coupon (1UO12) exposed in unfiltered B100 fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 39.61 55.79 4.59 Spectrum 2 Yes 28.18 63.82 7.99 Spectrum 3 Yes 37.83 55.10 7.07 Spectrum 4 Yes 100.00 Spectrum 5 Yes 35.58 55.53 8.89 Spectrum 6 Yes 36.33 47.20 16.47 Max. 39.61 63.82 100.00 Min. 28.18 47.20 4.59


142




Spectrum In stats. C O Mn Fe Spectrum 1 Yes 37.83 55.47 0.13 6.57 Spectrum 2 Yes 29.82 60.11 10.07 Spectrum 3 Yes 29.94 57.79 12.27 Spectrum 4 Yes 30.27 55.50 14.23 Spectrum 5 Yes 32.33 65.01 2.66 Max. 37.83 65.01 0.13 14.23 Min. 29.82 55.47 0.13 2.66


143




Spectrum In stats. C O Na Al Si Mn Fe Spectrum 1 Yes 27.78 55.24 0.32 16.66 Spectrum 2 Yes 24.47 64.08 1.90 2.05 2.17 5.33 Spectrum 3 Yes 26.76 67.11 6.12 Max. 27.78 67.11 1.90 2.05 2.17 0.32 16.66 Min. 24.47 55.24 1.90 2.05 2.17 0.32 5.33


144

Figure A21. SEM analysis of 1018 steel coupon (1FO12) exposed in filtered B100 fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 29.40 66.17 4.42 Spectrum 2 Yes 28.98 50.70 20.32 Spectrum 3 Yes 30.51 29.85 39.64 Spectrum 4 Yes 28.90 68.23 2.87 Spectrum 5 Yes 27.66 67.30 5.04 Spectrum 6 Yes 33.09 62.95 3.96 Spectrum 7 Yes 9.70 90.30 Spectrum 8 Yes 30.58 61.61 7.81 Spectrum 9 Yes 56.72 38.57 4.70 Max. 56.72 68.23 90.30 Min. 27.66 9.70 2.87


145




Spectrum In stats. C O Fe Spectrum 1 Yes 35.89 49.10 15.02 Spectrum 2 Yes 35.56 49.24 15.21 Spectrum 3 Yes 7.08 92.92 Spectrum 4 Yes 40.15 48.89 10.96 Spectrum 5 Yes 7.12 92.88 Max. 40.15 49.24 92.92 Min. 35.56 7.08 10.96


146




Spectrum In stats. C O Fe Spectrum 1 Yes 67.84 10.43 21.73 Spectrum 2 Yes 34.42 53.40 12.18 Spectrum 3 Yes 12.95 68.31 18.74 Spectrum 4 Yes 59.56 17.38 23.06 Spectrum 5 Yes 64.83 13.03 22.14 Spectrum 6 Yes 37.13 51.46 11.41 Spectrum 7 Yes 41.17 47.94 10.89 Spectrum 8 Yes 44.52 40.70 14.78 Spectrum 9 Yes 82.16 17.84 Spectrum 10 Yes 65.00 17.19 17.80 Max. 82.16 68.31 23.06 Min. 12.95 10.43 10.89


147




Spectrum In stats. C O Fe Spectrum 1 Yes 25.14 60.27 14.60 Spectrum 2 Yes 27.47 64.30 8.23 Spectrum 3 Yes 26.96 56.87 16.17 Spectrum 4 Yes 26.96 64.33 8.72 Spectrum 5 Yes 100.00 Max. 27.47 64.33 100.00 Min. 25.14 56.87 8.23


148




Spectrum In stats. C O Cr Fe Spectrum 1 Yes 67.57 10.94 21.49 Spectrum 2 Yes 67.18 5.57 27.24 Spectrum 3 Yes 49.97 30.10 19.93 Spectrum 4 Yes 51.38 28.21 20.40 Spectrum 5 Yes 60.70 22.36 0.28 16.67 Spectrum 6 Yes 34.83 13.67 51.50 Max. 67.57 30.10 0.28 51.50 Min. 34.83 5.57 0.28 16.67


149




Spectrum In stats. C O Mn Fe Spectrum 1 Yes 24.78 57.58 17.64 Spectrum 2 Yes 27.33 60.11 12.56 Spectrum 3 Yes 27.84 50.04 0.19 21.93 Spectrum 4 Yes 24.41 39.81 0.80 34.98 Spectrum 5 Yes 31.46 63.00 5.54 Spectrum 6 Yes 29.25 59.34 11.41 Spectrum 7 Yes 30.24 62.45 7.31 Spectrum 8 Yes 28.88 65.13 5.98 Spectrum 9 Yes 25.75 63.00 11.24 Max. 31.46 65.13 0.80 34.98 Min. 24.41 39.81 0.19 5.54


150

Figure A27. SEM analysis of 1018 steel coupon (3UC11) exposed in unfiltered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 54.09 27.33 18.58 Spectrum 2 Yes 45.75 33.63 20.62 Spectrum 3 Yes 75.06 15.73 9.22 Spectrum 4 Yes 36.15 51.37 12.48 Spectrum 5 Yes 53.00 35.29 11.71 Spectrum 6 Yes 49.56 36.05 14.39 Spectrum 7 Yes 40.31 43.37 16.32 Mean 50.56 34.68 14.76 Std. deviation 12.62 11.33 4.01 Max. 75.06 51.37 20.62 Min. 36.15 15.73 9.22


151

Figure A28. SEM analysis of 1018 steel coupon (3UO11) exposed in unfiltered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 77.25 19.94 2.80 Spectrum 2 Yes 47.59 10.62 41.79 Spectrum 3 Yes 72.87 22.24 4.89 Spectrum 4 Yes 74.27 22.96 2.77 Spectrum 5 Yes 78.08 19.12 2.80 Spectrum 6 Yes 75.76 19.55 4.70 Spectrum 7 Yes 85.80 12.01 2.19 Spectrum 8 Yes 79.84 14.39 5.77 Mean 73.93 17.60 8.46 Std. deviation 11.35 4.66 13.53 Max. 85.80 22.96 41.79 Min. 47.59 10.62 2.19


152

Figure A29. SEM analysis of 1018 steel coupon (3UM11) exposed in unfiltered ULSD fuel-

water mixture exposed in a selective aerobic environment.


Spectrum In stats. C O Fe Spectrum 1 Yes 74.78 14.89 10.33 Spectrum 2 Yes 76.04 16.68 7.29 Spectrum 3 Yes 73.58 20.03 6.39 Spectrum 4 Yes 61.99 28.15 9.86 Mean 71.60 19.94 8.47 Std. deviation 6.48 5.88 1.93 Max. 76.04 28.15 10.33 Min. 61.99 14.89 6.39


153

Figure A30. SEM analysis of 1018 steel coupon (3FC13) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 71.32 25.60 3.08 Spectrum 2 Yes 32.95 2.24 64.82 Spectrum 3 Yes 27.67 7.12 65.21 Spectrum 4 Yes 65.03 23.09 11.89 Spectrum 5 Yes 64.89 18.16 16.96 Mean 52.37 15.24 32.39 Std. deviation 20.39 10.15 30.19 Max. 71.32 25.60 65.21 Min. 27.67 2.24 3.08


154

Figure A31. SEM analysis of 1018 steel coupon (3FO12) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Fe Spectrum 1 Yes 51.02 40.89 8.09 Spectrum 2 Yes 52.81 27.17 20.02 Spectrum 3 Yes 41.00 26.42 32.58 Spectrum 4 Yes 14.29 4.34 81.37 Spectrum 5 Yes 56.99 34.73 8.28 Mean 43.22 26.71 30.07 Std. deviation 17.21 13.84 30.40 Max. 56.99 40.89 81.37 Min. 14.29 4.34 8.09


155

Figure A32. SEM analysis of 1018 steel coupon (3FM13) exposed in filtered ULSD fuel-water



Spectrum In stats. C O Fe Pd Spectrum 1 Yes 38.64 27.39 33.98 Spectrum 2 Yes 8.78 90.79 0.43 Spectrum 3 Yes 100.00 Spectrum 4 Yes 100.00 Spectrum 5 Yes 68.35 25.15 6.50 Spectrum 6 Yes 61.84 32.93 5.23 Max. 68.35 32.93 100.00 0.43 Min. 38.64 8.78 5.23 0.43


microbiologically influenced corrosion of 1018 …...iii abstract this research focuses on the...

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